BOLOGNA COURSE INFORMATION FORM

BOLOGNA COURSE INFORMATION FORM

Course Information

Year ofCurriculum

Course Title Code Semester L+P Hour Credits ECTS

1 Foreign English 1

BMB103 Güz 3+0 3 3

Language of Instruction Turkish

Course Level Undergraduate

Department/Program Bachelor Programme in Computer Engineering

Education Type Formal Education

Course Type Required

Prerequisites

Department/Program Coordinator

Instructors

Assistants

Objectives of the Course

Reading: Use of different reading strategies. Writing: Conveying ideas and thoughts without breaking the fluency of written structure, technical writing and identifying important writing blocks, summarizing and rewriting the written documents with our own wordsSpeaking and Listening: Following up the lecture given by the instructors easily and improving spoken English abilities at the level oftaking part in educational discussions on any thought and feeling of us in the class

Course Content

To learn the reading strategies intended to various types of written documents To improve the vocabulary knowledge by the help of types of written documents. Toexercise on speaking English.

Teaching-Learning Methods and Techniques Used in the Course

Internship of the Course(If there is)

Learning Outcomes

Students shall make predictions on the texts at a glance before reading it; skim texts and deduce the main

1

idea and read for implied meaning between the lines, deduce the main ideas from the whole text

Student shall adapt different reading strategies to different types of texts and write essays about an issueat hand; write introduction-body-conclusion paragraphs which are consistent and coherent.

Students acquire the ability to make text translation.

COURSE CONTENT

Week Topics

1 İntroduction

2 Unit 1 – Reading 1






8 Midterm I





13 Unit 5 – Reading 2, Midterm 2


15 Final Exam

RECOMMENDED SOURCES

Brenda Bushhell ,Brenda Dyer, 2003. Global Outlook, Mc Graw Hill Publishers, Modern Diller öğretim görevlilerinin hazırlamış olduğu materyal, Written materials that is prepared by instructors of Modern Languages Department.

ASSESSMENT

IN-TERM STUDIES QUANTITY PERCENTAGE

Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice

Internship of the Course

2

Project

Field Survey

Workshop

Laboratory

Presentation

Final examination 1 60

Total 2 100

Contribution of Semester Studies to the Success Grade 1 40

Contribution of the Final Exam to the Success Grade 1 60

Total 2 100

ECTS/WORKLOAD TABLE

Activities QuantityDuration(Hour)

TotalWorkload

(Hour)

Ders Süresi (Sınav haftası dahildir: 15x toplam ders saati) 15 2 30

Sınıf Dışı Ders Çalışma Süresi (Ön çalışma, pekiştirme) 5 2 10

Ödev 5 6 30

Seminer

Sunum

Uygulama

Laboratuvar

Derse Özgü Staj (varsa)

Proje

Arazi Çalışması

Atölye Çalışması

Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav

Yarıyıl Sonu Sınavı 1 10 10

Toplam İş Yükü 22 24 90

Toplam İş Yükü / 30 (s) 3

Dersin AKTS Kredisi 3

ASSOCIATING THE LEARNING OUTCOMES OF THE COURSE WITH THE PROGRAM OUTCOMES

Course Learning

Outcomes

PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO1

0CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x x

3

CLO5 x x x

4


Course Information

Year ofCurriculum


1 Physics I BMB104 Autumn 3+1 4 5






Prerequisites


Instructors

Assistants


To introduce the fundamental principles and concepts of physics in

detail at freshmen level. To build a strong background for physics

major as well as showing the necessity and importance of physics for

other branches of natural sciences and

engineering through applications in real life, and industry and

technology.

Course Content

Physics and Measurement, Vectors, Motion in One Dimension,

Motion in Two Dimensions, The Laws of Motion, Circular Motion and

other Applications of Newton’s Laws, Work and Kinetic Energy,

Potential Energy and Conservation of Energy, Linear Momentum and

Collisions, Rotation of a Rigid Object About a Fixed Axis, Rotation of a

Rigid Object About a Moving Axis, Torque and Angular

Momentum, Statik Equilibrium and Elasticity, Oscillatory Motion.



1

Learning Outcomes

1. Students would have up to date information, software, theoretical and practical knowledge

on Physics. Moreover, they will be equipped with knowledge sufficiently to use Physics related resources.

2. Students would acquire theoretical knowledge on subject of Physics theories.

3. They could apply the theoretical knowledge gained in the field of Physics

4. Students would be able to analyze the experimental results.

5. They would acquire the ability to figure out the physical concepts and issues in the field of

Physics through scientific methods and interprete them.

COURSE CONTENT

Week Topics

1 Physics and Measurements, Vectors

2 Motion and Kinematic Equations (1D, 2D Motion)

3 The Laws of Motion

4 Circular Motion & Other Applications of Newton’s Law

5 Work & Kinetic Energy, Potential Energy & Conservation of Energy

6 Potential Energy & Conservation of Energy

7 Linear Momentum & Collisions

8 Mid Term Exam

9 Linear Momentum & Collisions

10 Rotation of a Rigid Object About a Fixed Axis

11 Rotation of a Rigid Object About a Fixed Axis

12 Rotational Motion and Angular Momentum

13 Rotaional Motion and Angular Momentum, Static Equilibrium

14 Vibrational Motion

15 Final Exam

RECOMMENDED SOURCES

- Serway-Beichner, Physics-5th Edition- Fundamentals of Physics, David Halliday-Robert Resnick- Sears ve Zemansky, University Physics, Pearson Education Yayıncılık, 2009- Physics, Giancoli, Akademi Yayın, 2009

Physics 1, Frederick J.Keller, W.Edward Gettys, Malcolm J. SkoveASSESSMENT


Mid-terms 1 40

Quizzes

2

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





3


Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x xCLO5 x x x

4

BOLOGNA DERS İÇERİK FORMU

DERS BİLGİLERİ

MüfredatYılı

Ders Adı Kodu Yarıyıl T+U Saat Kredi AKTS

1 Linear Algebra BMB105 Autumn 2+1 4 6

Dersin Dili Türkçe

Dersin Düzeyi Lisans

Bölümü/Programı Bilgisayar Mühendisliği Lisans Bölümü

Öğrenim Türü Örgün Eğitim

Dersin Türü Zorunlu

Ön Koşul Dersleri

Bölüm/ProgramKoordinatörü

Dersin Sorumlusu (ları)

Dersin Yardımcıları

Dersin Amacı Create the necessary information for more advanced mathematics topics

Dersin İçeriği -Matrices: Definition of matrix, Types of matrices, matrix equality, Sum

and difference of matrices, The product of scaler and matrix and their

properties , Transpose of matrix and its properties - Some Special

Matrices and Matrix Applications - Elementary row and column

operations in matrices, Reduced row–echelon form, Rank of a matrix,

The inverse of a square matrix, - Determinants: The determinant of a

square matrix, Laplace's expansion, Properties of determinants -Sarrus

rule, Additional matrix, Calculation of the inverse of a matrix with the aid

of additional matrix - Systems of Linear Equations: Solving systems of

linear equations with the aid of equivalent matrices, Linear homogeneous

equations, -Cramer's method, The solution with the help of coefficients

matrix -Vectors: Vector definition, the sum of vectors, the difference, the

analytical expression vectors, scalar product of vectors, properties of the

scalar multiplication Scalar product and its features, the mixed

multiplication and properties, and properties of double vector product, -

Vector spaces: Definition of vector spaces and theorems. Subspaces.

Span concept and fundamental theorems. Linear dependence and linear

independence of vectors and some theorems about linear dependence

and linear independence. -Bases and dimension concepts and

fundamental theorems. Definition of coordinates and transition matrices

and some theorems. -Eigenvalues and Eigenvectors: The Calculation of

Eigenvalues and Eigenvectors of a square matrix, - The calculation of

Inverse and power of a square matrix with the help of the Cayley-

Hamilton

1

theorem.

Derste Kullanılan Öğretme-Öğrenme Yöntem ve Teknikleri

Dersin Staj Durumu

Dersin Öğrenme Çıktıları

1. On successful completion of this course unit students will be capable of gained the ability to; perform

matrix operations (addition, subtraction,multiplication). Compute the determinant of a given matrix,

2. Solve systems of linear equations by using Gaussian elimination; and apply the basic techniques of matrix algebra, including finding the inverse of an invertible matrix using Gauss-Jordan elimination,

3. Understand the basic ideas of vector algebra: linear dependence and independence; comprehend vector spaces and subspaces,

4. Find the eigenvalues and eigenvectors of a square matrix using the characteristic polynomial,

5. Calculate the inverse and n-th power of a square matrix by using Cayley-Hamilton theorem.

6.

7.

8.

DERS AKIŞI

Hafta Konular

1

Definition of matrix, types of matrix, Equality of Matrices, Addition and subtraction of matrices, matrix multiplication by a scalar, Some properties about them. Multiplying matrices and Some properties about it. Transposes of matrices and properties of thetranspose.

2

Some Special Matrices and matrix applications.(Symmetric Matrix,Anti symmetric matrix, periodic matrix, idempotent matrix, Nilpotent matrix, orthogonal matrix, A conjugate of a matrix and its properties, hermitian matrix,Anti hermitian matrix, regular matrix,singuler matrix, and their applications.

3Elementary row and column operations in the Matrices. Row- Echelon form and reduced row-echelon form. Rank of a matrix.Inverses of matrices and some applications about this.

4Definition of a determinant. Laplace expansion of a matrix.Properties of a determinant.

5Rule of Sarrus. The adjoint of a matrix, Using the adjoint matrix tofind an inverse matrix and some applications about this.

6System of linear equations: solving systems of linear equations with aid of equaivalent matrices, linear homogeneous equations andsome applications about this.

7Cramer’s rule. Using the inverse of a coefficient matrix to solve alinear systems and some applications about this.

8 Midterm Exam

2

9

Vectors: Definition of Vectors,The sum of vectors and Subtraction of vectors and Multiplication of vectors, Dot product of two vectors and their properties, Vector product of two vectors(Cross product of vectors ) and their properties, Mixed product of three vectors(Triple product) and their properties, Double vector product(double cross)and their properties and some applications about this.

10Vector Spaces: Definition of vector spaces and theorems.Subspaces and their applications.

11

Span concept and fundamental theorems. Linear dependence and linear independence of vectors and some theorems about linear dependence and linear independence. Some applications aboutthis.

12Quiz, Bases and dimension concepts and fundamental theorems.Some applications about this.

13Definition of coordinates and transition matrices and sometheorems.Some applications about this.

14Eigenvalues and eigenvectors: The eigenvalues of a squarematrix.Cayley Hamilton Theorem and their applications.

15 Final

KAYNAKLAR

-Anton Howard, “Elementary Linear Algebra”, 2000

-Lineer Cebir ve Çözümlü Problemleri\Linear Algebra and Solving Problems (Güncelleştirilmiş Baskı),

Prof. Dr. A. Göksel AĞARGÜN, Yrd. Doç. Dr. Hülya BURHANZADE, Birsen Yayınevi, İstanbul 2015

-Lineer Cebir Çözümlü Problemleri” ,Doç.Dr.Gürsel Yeşilot

-Bernard Kolman, David, R, Hill, “Uygulamalı lineer Cebir” Prof.Dr.Ömer Akın,

Palme Yay., 2002 \Applied Linear Algebra

DEĞERLENDİRME SİSTEMİ

YARIYIL İÇİ ÇALIŞMALARI SAYISI KATKI YÜZDESİ

Ara Sınav 1 40

Kısa Sınav

Ödev

Devam

Seminer

Uygulama


3

Proje

Arazi Çalışması


Laboratuvar

Sunum

Yarıyıl Sonu Sınavı 1 60

Toplam2 100

Yarıyıl İçi Çalışmalarının Başarı Notuna Katkısı 1 40

Yarıyıl Sonu Sınavının Başarı Notuna Katkısı 1 60

Toplam 2 100

AKTS / İŞ YÜKÜ TABLOSU

Etkinlik SAYISISüresi(Saat)

Toplamİş Yükü(Saat)



Ödev 10 3 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





DERSİN ÖĞRENME ÇIKTILARININ PROGRAM ÇIKTILARI İLE İLİŞKİLENDİRİLMESİ

Öğrenme Çıktıları PÇ1 PÇ2 PÇ3 PÇ4 PÇ5 PÇ6 PÇ7 PÇ8 PÇ9 PÇ10ÖÇ1. x x xÖÇ2. x x xÖÇ3. x x x xÖÇ4. x x xÖÇ5. x x x

4


Course Information

Year ofCurriculum


1 Mathematics I BMB106 Autumn 2+1 4 6






Prerequisites


Instructors

Assistants

Objectives of the CourseTo give information of foundation of Mathematics and to satisfy properties of analytical thinking.

Course Content Functions:Domain of a function,Functions and Graphs, Even-Odd Functions, Symmetry, Operations on Functions (Sum, difference, multiğlication, division and powers),Composite functions, Piecewise Functions, polynomials and Rational Functions, Trigonometric functions Limits and Contiunity: Limit of a Function and Limit Laws, The Sandwich (The Squeeze theorem), The Precise Definition of a Limit, One-sided Limits, , Limits İnvolving İnfinity, Infinity limits,Contiunityat a point, Continuous Functions, The İntermediate Value Theorem Types of Discontiunity, Differentiation:Tangents ,Normal Lines , The Derivative at a Point, The Derivate as a Function, One-sided Derivatives,Differentiable on an İnterval, , Differentiation Rules, High order Derivatives, Derivativesof Trigonometric Fnctions, The chain rule, Implicit Differentiation, Linearization and Differentials, Increasing Functions and Decrasing Functions,Transcendental Functions:Inverse Functions and Their Derivatives,Logarithms and Exponential Functions and Their Derivatives, Logarithmic Differentiation, Inverse Trigonometric Functions and Their Derivatives, Hyperbolic Functions and Their Derivatives,Inverse Hyperbolic Functions and Their Derivatives,Indeterminate Forms and L’Hospitals Rule, Extrem Values of Functions, Critical Points,Rolle’s Theorem, The Mean Value Theorem, The First Derivative Test for Local Extrema, Concavity , The Second Derivative Test for Concavity, Point of İnflection, The Second Derivative Test for Local Extrema,Asymptotes of Graphs Graphing of y=f(x), Antiderivatives, Indefinite İntegrals, Integral table,Integration:Area and Estimating with Finite Sums, Sigma Notation

1

and Limits of Finite Sums, Riemann Sums, Definite İntegral, Properties ofDefinite İntegral, Area Under the Graph of a nonnegative Function, Average Value of Continuous Functions,Mean Value Theorem fo Definite İntegrals, The Fundamental Theorem of Calculus: Fundamental Theorem Part 1, Fundamental Theorem Part 2, Techniques of Integration: Integration by Substitution, Integration by Parts, Trigonometric Integrals,Reduction Formulas,Trigonometrik Substitutions, Tan (θ/2) subtitutions, Integrations of Rational Functions by Partial Fractions,Applications of definite integrals:Area between two curves, Volumes Using Cross-sections, The Disk Method, the Washer Method, The Ccylindrical Shell method, Arch Length, Areas of Surfuces of Revolution,Improper Integrals,Improper Integrals of Type 1 and Type 2



Learning Outcomes

1. Students will learn using the concepts of limit, continuity and differetation of one variable functions,

2. Students will learn sketching the graph of a function using asymptotes, critical points and the derivative test for increasing/decreasing and concavity properties,

3. Students will learn setting up and solving max/min problems,

4. Students will learn evaluating definite integrals by using the Fundamental Theorem of Calculus and evaluating areas, volumes and arc lenghts by mean of definit integral,

5. Students will learn applying techniques of integration and working with transcendental functions.

COURSE CONTENT

Week Topics

1

Functions:Domain of a Function,Functions and Graphs, Even-Odd Functions, Symmetry, Operations on Functions (Sum, difference, multiplication, division and powers),Composite Functions, Piecewise Functions, Polynomials and Rational Functions,

Trigonometric Functions

2

Limits and Contiunity: Limit of a Function and Limit Laws, The Sandwich (The Squeeze theorem), The Precise Definition of a Limit,

One-sided Limits, , Limits İnvolving İnfinity, Infinity Limits

3

Contiunity at a Point, Continuous Functions, The İntermediate Value Theorem Types of Discontiunity, Differentiation:Tangents ,Normal Lines , The Derivative at a Point, The Derivate as a Function,

Onesided Derivatives

4

Differentiable on an Interval, Differentiation Rules, High order Derivatives, Derivatives of Trigonometric Functions, The Chain Rule, Implicit Differentiation, Linearization and Differentials,

Increasing Functions and Decrasing Functions

2

5

Transcendental Functions:Inverse Functions and Their Derivatives,Logarithms and Exponential Functions and Their Derivatives, Logarithmic Differentiation, Inverse Trigonometric Functions and Their Derivatives, Hyperbolic Functions and Their

Derivatives,Inverse Hyperbolic Functions and Their Derivatives

6Indeterminate Forms and L’Hospitals Rule, Extrem Values of

Functions, Critical Points,

7

Rolle’s Theorem, The Mean Value Theorem, The First Derivative Test for Local Extrema, Concavity , The Second Derivative Test for Concavity, Point of İnflection, TheSecond Derivative Test for Local

Extrema

8 Midterm 1

9Asymptotes of Graphs, Curve Sketching, Antiderivatives, Indefinite

Integrals, Integral Tables

10

Integration:Area and Estimating with Finite Sums, Sigma Notation and Limits of Finite Sums, Riemann Sums, Definite İntegral, Properties of Definite İntegral, Area Under the Graph of a

nonnegative Function, Average Value of Continuous Functions

11

Mean Value Theorem fo Definite İntegrals, The Fundamental Theorem of Calculus: Fundamental Theorem Part 1, Fundamental Theorem Part 2, Techniques of Integration: Integration by Substitution, Integration by Parts, Trigonometric Integrals,

Reduction Formulas

12Quizz 1, Trigonometric Substitutions, Tan (θ/2) subtitutions,

Integrations of Rational Functions by Partial Fractions

13

Applications of definite integrals:Area between two curves, Volumes Using Cross-sections, The Disk Method, the Washer Method, The Ccylindrical Shell method, Arch Length, Areas of Surfuces of

Revolution

14 Improper Integrals, Improper Integrals of Type 1 and Type 2

15 Final Exam

RECOMMENDED SOURCES

-1.Thomas’ Calculus, 12th Edition, G.B Thomas, M.D.Weir, J.Hass and F.R.Giordano, Addison-Wesley, 2012.-2.Calculus: A Complete Course, Robert A. Adams,C Essex 7th Edition,AddisonWesley Longman Toronto 2010.

ASSESSMENT


Mid-terms 1 40

3

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 10 3 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





4


Course Learning

Outcomes



5


Course Information

Year ofCurriculum


1 Computer Programming I

BMB107 Autumn 2+1 3 4






Prerequisites None


Instructors

Assistants


This is a good course for those with little or no programming experience. Students develop skills to program and use computational techniques to solve problems. Topics include the notion of computation, simple algorithms and data structures, using an editor, program design, implementation with Python, testing and debugging, and algorithmic complexity.

Course Content

Software, hardware, problem solving (algorithms and pseudocode), Python programming language, input and output operations, variables, arithmetic and data types, conditional statements, loops, scoping, collections, introduction to functions and recursion.


Classroom discussion and computer laboratory work.


Learning Outcomes

1. Ability to construct flowcharts and pseudocodes of the algorithms

2. Ability to use basic algorithm structures.

3. Ability to understand and develop computer code using input-output operators, variables, conditional operators and loops.

4. To understand the use of functions.

1

5. Ability to understand the use of collections.

6. Ability to understand the concept and use of recursion.

7. Ability to construct basic computer code with functions and collections.

COURSE CONTENT

Week Topics

1Basic computer systems, software, hardware, assembler, machine language, high level languages,

2 Algorithms

3 Algorithms and pseudocodes.

4Introduction to C, input/output, comments, variables, declaration of variables, built-in data types arithmetic operators.

5 Conditional statements

6 Loops (while-loop, for-loop)

7 Nesting, break and continue statements, logical operators.

8 Midterm Exam

9 Lists

10 Input and Output

11 Introduction to functions.

12 Passing lists (i.e. one dimensional arrays) to functions.

13 Recursion

14 Recursion

15 Final Exam

RECOMMENDED SOURCES

C Programming Language: Brian W. Kernighan, Dennis M. Ritchie, Rifat Çölkesen

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework 1 10

Attendance

Practice

Seminar

Practice


2

Project

Field Survey

Workshop

Laboratory

Presentation 1 60


Total 2 40



Total 1 30

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)

Course Duration (Including the exam week: 15x Total course hours)

15 2 30

Hours for off-the-classroom study (Pre-study, practice)

Homework 5 8 40

Seminar

Presentation

Practice 15 1 15

Laboratory 10 10 10


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 9 9

Quizzes

Homework(s)/Seminar(s) 1 16 16

Final examination 120

Total Work Load 4.00

Total Work Load / 30 (h) 4

ECTS Credit of the Course 15 2 30


Course Learning

Outcomes


0CLO1 x x x

3

CLO2 x x xCLO3 x xCLO4 x x xCLO5 x xCLO6 x xCLO7 x x x x

4


Course Information

Year ofCurriculum


2Introduction to Visual Programming

BMB201 Spring 3+2 4 6






Prerequisites None


Instructors

Assistants


To teach the student the visual programming language knowledge and the C # programming language. At the end of the course, the student willhave the knowledge of developing visual programs in C # programming language, accessing data sources and developing database applications.

Course Content

Introduction to programming and .NET platform, Visual Studio setup and environment, project preparation steps, data types, decision structures and loops in Visual C # programming language, returning and non-returning methods, exception management, object-oriented programming, Windows forms and controls, database addition , creating Windows applications by developing interfaces.



Learning Outcomes

1.To be able to establish and use a visual programming language

2. Recognizing the interface (IDE) environment

3. To be able to distinguish the objective programming structure from structured programming.

1

4. To be able to use basic components and arrange them visually.

5. . To be able to use variables, control statements and loops in program writing.

6. . To be able to comprehend and use terms and definitions related to the concept of class and objectafter using an objective language.

COURSE CONTENT

Week Topics

1 Visual programming working environment (IDE).

2 Introduction to Object Oriented Programming

3 Object Models and Classes

4 Data types, variables, constants, control statements and loops.

5 Writing and using function-procedure. Use of ready functions.

6 Message windows and information entry boxes

7 Basic Component properties and uses.

8 Midterm Exam

9 Events / Forms. Form Properties (Main - Baby Form).

10 Menu and toolbar controls.

11 Dialog Boxes.

12 Error detection techniques. Try / Except, Try / Finally

13 Creating sample interfaces

14 Project development

15 Final Exam

RECOMMENDED SOURCES

ASSESSMENT


Mid-terms 1 30

2

Quizzes

Homework 1 10

Attendance

Practice

Seminar

Practice

Internship of the Course 1 20

Project

Field Survey

Workshop

Laboratory

Presentation 1 40

Final examination

Total 2 40



Total 1 30

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60

Hours for off-the-classroom study (Pre-study, practice) 10 4 40

Homework 10 2 20

Seminar

Presentation

Practice 10 4 40

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 8 8

Quizzes





3



Course Learning

Outcomes


0CLO1 x x x x

CLO2 x x xCLO3 x x x xCLO4 x x x x xCLO5 x x x x xCLO6 x x x x x

4


Course Information

Year ofCurriculum


1 Turkish Language II







Prerequisites


Instructors

Assistants

Objectives of the CourseCorrect use of Turkish, reading the professional and extraprofessional texts, successful oral and written expression.

Course ContentReading sample literary and contemporary texts. Oral and written expression.



Learning Outcomes

Know about the languages used in the world and the place of Turkish among world languages.

Acquires the correct use of spelling rules and punctuation marks

Acquires a larger vocabulary

Can use science and knowledge in a better way.

Acquires reading habit and pleasure

1

COURSE CONTENT

Week Topics

1 Introduction to written genres.

2 Text analysis:Poem.

3 Text analysis: Story.

4 Text analysis: Fiction.

5 Genres dealing with the daily life (essay).

6 Samples of written genres (Biography, autobiography).

7 Samples of verbal expression (conference, symposium)

8 Mid-term exam.

9 Correction of expression disorders, exercises.

10 CV.

11 Punctuation exercises.

12The rules need to be considered in the prepared speech. Rules ofpronunciation, style and the tone in public.

13 Presantation exercises.



RECOMMENDED SOURCES

Class notesYusuf Çotuksöken, Üniversite Öğrencileri İçin Uygulamalı Türk Dili 1. ve 2. Cilt, Papatya Yayıncılık, İstanbul 2001.Doğan Aksan, Türkiye Türkçesinin Dünü, Bugünü, Yarını, Bilgi Yayınları,İstanbul 2000.T. Nejat Gencan, Dilbilgisi, Ayraç Yayınları, Ankara.Doğan Aksan, Türkçenin Sözvarlığı, Engin Yayınları, Ankara.Doğan Aksan, Türkçenin Gücü, Bilgi Yayınevi, 4. Basım, Ankara 1997.Ömer A. Aksoy, Dil Yanlışları, Adam Yayıncılık, İstanbul 1999.Feyza Hepçilingirler, Türkçe “Off”, Remzi Yayınları.Talat Tekin-Mehmet Ölmez, Türk Dilleri/ Giriş, Simurg Yayınları, İstanbul 1999.Yazım Kılavuzu, Türk Dil Kurumu, 2012, Ankara.Necmiye Alpay, Türkçe Sorunları Kılavuzu, Metis Yayınları, İstanbul 2000.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

2

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev

Seminer

Sunum

Uygulama

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes


0

3

CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x xCLO5 x x x

4


Course Information

Year ofCurriculum


1 Foreign English 1







Prerequisites


Instructors

Assistants



Course Content




Learning Outcomes

Students will be able to answer open-ended questions in written forms and verbally.

Students will be able to write paragraphs consisted of topic sentences and supporting sentences.

1

Students will be able to comprehend the text by using reading strategies

Students will be able to accurately pronounce the vocabulary items and will be able to make sentences with them

COURSE CONTENT

Week Topics

1

CH 5: The Science of Nutrition p.118-122 o Gearing Up A+B o Video + discussion questions o Vocabulary Build p.120-122 (up topart B, While you read)

2CH 5: The Science of Nutrition p.122-127 o While you read p. 122 oReading 1 Diets Focusing on Macronutrient Composition...

3CH 5: The Science of Nutrition o Worksheet 1: Annotating andWriting a Summary o Reading 3: Losing Weight, Gaining Life.

4

CH 6: Digital Currencies p.150-159 o Gearing up p.150-151 o Vocabulary build p. 152,153,159 o Reading 2: FAQs from theBitcoin Website

5CH 6: Digital Currencies p.159 o Feedback session for summaries.o Reading 1: Digital cash for a Digital Age

6 Midterm 1

7CH 7: The Internet of Things p.178-185 o Gearing up p.178-179 oVocabulary build p. 180-181 o Reading 1: The Internet of Things

8 Midterm I

9CH 7: The Internet of Things p.191-195 o Reading Critically and Responding to a text. o Reading 2: Too Clever for Comfort

10Writing input – Combining all Worksheet 3: Writing to reflect (and persuade readers why your point is plausible)

11Writing practice For Mon, Wed, Thu, Fri classes: In-class writing(group work) + Feedback for group papers Tuesday classes are off.

12Writing Practice For Tuesday classes: In class writing and feedback (group work) For Mon, Thu, Fri classes: Individual writing practice Wednesday classes are off.

13

In-class feedback For Tuesday classes: Individual writing practice For Wednesday classes: Individual writing practice For Mon, Thu,Fri classes: In-class feedback sessions for individual papers

14In-class feedback + Catch-up Feedback sessions for Tuesday andWednesday classes Catch-up week for other classes

15 Final Exam

RECOMMENDED SOURCES

Leap 3 (New Edition) Reading & Writing Julia Williams - Pearson

ASSESSMENT

2


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer 5 12 60

Sunum

Uygulama

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





3


Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x x x

4


Course Information

Year ofCurriculum


1 Physics I BMB204 Spring 3+1 4 5






Prerequisites


Instructors

Assistants


To introduce the fundamental principles and concepts of physics in detail at freshmen level. To show the necessity and importance of physics for other branches of natural sciences and engineering through applications in real life, and industry and technology.

Course Content

Electric Fields; Gauss’s Law; Electric Potential; Capacitance and Dielectrics; Current and Resistance; Direct Current Circuits; Magnetic Field; Sources of the

Magnetic Field; Faraday’s Law; Inductance; Alternating Current Circuits.



Learning Outcomes

1. Students would have up to date information, software, theoretical and practical knowledge

on Physics. Moreover, they will be equipped with knowledge sufficiently to use Physics

1

related resources.2. Students would acquire theoretical knowledge on subject of Physics theories.

3. They could apply the theoretical knowledge gained in the field of Physics

4. Students would be able to analyze the experimental results.

5. They would acquire the ability to figure out the physical concepts and issues in the field of

Physics through scientific methods and interprete them.

COURSE CONTENT

Week Topics

1 Electric Fields

2 Gauss’ s Law

3 Electric Potential

4 Electric Potential, Capacitance and Dielectrics

5 Capacitance and Dielectrics

6 Current and Resistance, Direct Current Circuits

7 Direct Current Circuits

8 Mid Term Exam

9 Magnetic Fileds

10 Sources of Magnetic Field

11 Sources of Magnetic Field

12 Faraday’ s Law

13 Inductance

14 Alternating Current Circuits

15 Final

RECOMMENDED SOURCES

- Serway-Beichner, Physics-5th Edition- Fundamentals of Physics, David Halliday-Robert Resnick- Sears ve Zemansky, University Physics, Pearson Education Yayıncılık, 2009- Physics, Giancoli, Akademi Yayın, 2009

Physics 1, Frederick J.Keller, W.Edward Gettys, Malcolm J. SkoveASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

2

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO1

3

Outcomes 0CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x xCLO5 x x x

4


Course Information

Year ofCurriculum


1 Informatics Ethics

BMB205 Bahar 2+0 2 2





Course Type Elective

Prerequisites None


Instructors

Assistants

Objectives of the CourseThe main aim of the course is to improve the level of concept knowledge and practical implementation skills of teacher candidates on generating solutions to current problems of informatics ethics and IT security.

Course Content

Ethics as a concept; historical development of computer security; relationship between ethics and vocation, professional ethics; the nature of ethical principles; ethical responsibilities of digital citizenship and information society; ethical problems in the use of information resources;accuracy of information; access to information; privacy; data protection; intellectual property, copyright, patents and license agreements; IT law; cyber crimes; social effects of it crimes; basic concepts of cyberspace andcybersecurity; cyber actors and attack methods; cyber defense methods;security in mobile and social media environments; network security; personal and institutional data security management; informatics legislation and law.



Learning Outcomes

1. To explain technological and pedagogical knowledge for problems related to computer security and informatics ethics.

1

2. To generate solutions for social conflicts of the information age.

3. To explain ethical theories in computer education.

4. To develop strategies for ethics education of the next generation.

COURSE CONTENT

Week Topics

1Introduction to course ● Descriptions ● Content ● Weekly schedule ● Assesment policy ● Recommended resources

2Ethics as a concept, ethical theory, basic philosophical approaches, the relationship among ethics, morality and law. Ethical practices in social life. Professional ethics.

3 Informatics ethics as an ethical branch, history of informatics ethics.

4The importance of individual responsibilities in the context of using application in digital setting.

5 Four ethical issues of Information age

6 The case samples used for informatics ethics education.

7 The steps of process towards solving ethical issues.

8 Midterm 1

9 Midterm Exam

10 Personal and instutional data security management; informatics legislation and law.

11Basic concepts of cyber space and cyber security; cyber actors and attack methods; cyber defense methods.

12 Security and ethics in mobile and social media environments, network security.

13 Project review

14 Project review

15 Final

RECOMMENDED SOURCES

Barger, R. N. (2008). Computer ethics: A case-based approach. New York, NY: Cambridge UniversityPress.• Mason, R. O. (1986). Four ethical issues of information age. MIS Quarterly, 10,(1), 5-12.Bynum, T. (2001). Computer ethics: Its birth and its future. Ethics and Information Technology, 3(2), 109–112.• Kert, S.-B., Uz, C., & Gecü, Z. (2014). Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education. Educational Technology & Society, 17 (3), 320–331.

2

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Practice

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation 1 60


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 2 30


Homework

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


3






Course Learning

Outcomes


0CLO1 xCLO2 x xCLO3 xCLO4 x

4


Course Information

Year ofCurriculum


1 Mathematics I BMB206 Spring 2+1 4 5






Prerequisites


Instructors

Assistants

Objectives of the CourseTo give a broad knowledge and basic understanding of sequences and series and to gain ability of using the concepts of limit, continuity, partial differentiation , double integrals

Course Content Infinite Sequences : Convergence and Divergence of Sequences, Calculating limit of sequences, The Sandwich Theorem for Sequences, The Continuous Function Theorem for Sequences, Commonly Occurring Limits, Recursive Definitions, Bounded Monotonic Sequences, Monotonic Sequences Theorem .Infinite Series: Geometric Series, The nth-Term Test for a Divergent Series, Combining Series, Adding or Deleting Terms, Convergence Tests For Positive Series: The Integral Test , P-Series , Harmonic Series, The Comparison Test , The Limit Comparison Test , TheRatio Test , The Root Test. Alternating Series : Alternating Harmonic Series , The Alternating Series Test(Leibniz’s Test) , Absolute and Conditional Convergence. Power Series : The Radious of Convergence of a Power Series, Operations on Power Series ,The Series Multiplication Theorem for Power Series , The Term-by-Term Differentiation Theorem , The Term-by Term Integration Theorem,Taylor and Maclaurin Series, Taylor Polynomial of order n. Applications of Taylor Series: Evaluating non Elementary Integrals, Arctangents, Evaluating Indeterminate Forms. Parametric Equations and Polar Coordinates: Parametrizations of Plane Curves , Parametric Equations , Calculus With Parametric Curves: Derivative,Length of Parametrically Defined Curve.Polar Coordinates: Polar Equations , Relating Polar and Cartesian Coordinates, Graphing in Polar Coordinates (line, circle, cardioid), Areas and Lengths in Polar Coordinates : Area in the Plane, Length of a Polar Curve.Vectors: Three-

1

Dimensional Coordinate Systems, Vectors, The Dot Product, Angle Between Two Vectors, Perpendicular Vectors, The Cross Product, Parallel Vectors. Lines and Line Segments in Space: Vectors Equation for a Line, Parametric Equations for a Line, An Equation for a Plane in Space, Lines of Intersection.Vector-Valued Functions:Curves in Space and Their Tangents, Limits and Continuity, Derivatives,Velocity Vector,Acceleration Vector,Differentiation Rules,Arc Length Along a Space Curve.Functions of Several Variables: Domains and Ranges , Functions of Two Variables ,Graphs and Level Curves of Functions of Two Variables,Functions of Three Variables, Level surfaces (plane, sphere, cone, eliptic paraboloid, ellipsoid, cylinder), Limits for Functions of Two Variables, Continuity, Two-Path Test for Nonexistence of a Limit , Continuity of Composites, Functions of More Than Two Variables.Partial Derivatives: Partial Derivaties of two variables functions, Partial Derivatives and Continuity, Second-Order Partial Derivatives,Partial Derivatives of Still Higher Order, Differentiability,The Chain Rule: Functions of Two Variables , Chain Rule for Functions of two Independent Variables, Functions of Three Variables, Chain Rule for Functions of ThreeIndependent Variables, Chain Rule for Two Independent Variables and Three Intermediate Variables.Implicit Differentiation Revisited. DirectionalDerivatives and Gradient Vectors : Directional Derivatives in the Plane , Interpretation of the Directional Derivative , Calculation and Gradients , Gradients and Tangents to Level Curves , Functions of Three Variables, Tangent Planes and Differentials: Tangent Plane of The Surface, The Normal Line of The Surface.The Linearization of a Function of two Variables, Differentials . Extreme Values: Local Extreme Values, First Derivative Test for Local Extreme Values, Critical Point, Saddle Point, Second Derivative Test for Local Extreme Values. Double Integrals : Double andIterated Integrals over Rectangles, Double Integrals as Volumes, Fubini’s Theorem (First Form), Double Integrals over General Regions , Double Integrals over Bounded Nonrectangular Regions , Volumes (volumes between two surfaces), Fubini’s Theorem (Stronger Form) .Finding Limits of Integration :Using Vertical Cross-sections , Using Horizontal Cross-sections , Properties of Double Integrals, Area by Double Integration, Average Value Theorem, Double Integrals in Polar Form: Finding Limits ofIntegration, Changing Cartesian Integrals into Polar Integrals. Calculatingvolumes by using polar coordinates (volume between two surfaces), Substitutions in Double Integrals.



Learning Outcomes

1. Students will learn using the concepts of limit, continuity and differetation of one variable functions,

2. Students will learn sketching the graph of a function using asymptotes, critical points and the derivative test for increasing/decreasing and concavity properties,

3. Students will learn setting up and solving max/min problems,

4. Students will learn evaluating definite integrals by using the Fundamental Theorem of Calculus and evaluating areas, volumes and arc lenghts by mean of definit integral,

5. Students will learn applying techniques of integration and working with transcendental

2

functions.

COURSE CONTENT

Week Topics

1

Infinite Sequences : Convergence and Divergence of Sequences, Calculating limit of

sequences, The Sandwich Theorem for Sequences, The Continuous Function Theorem for

Sequences, Commonly Occurring Limits, Recursive Definitions, Bounded

Monotonic Sequences, Monotonic Sequences Theorem .

2

Infinite Series: Geometric Series, The nth-Term Test for a Divergent Series, Combining Series,

Adding or Deleting Terms, Convergence Tests For Positive Series: The Integral Test , P-Series ,

Harmonic Series, The Comparison Test , The Limit Comparison Test , The

Ratio Test , The Root Test.

3

Alternating Series : Alternating Harmonic Series , The Alternating Series Test(Leibniz’s Test) ,

Absolute and Conditional Convergence. Power Series : The Radious of Convergence of a

Power Series, Operations on Power Series ,The Series Multiplication Theorem for Power

Series , The Term-by-Term Differentiation Theorem , The Term-by Term Integration

Theorem,Taylor and Maclaurin Series, Taylor Polynomial of order n.

4

Applications of Taylor Series: Evaluating non Elementary Integrals, Arctangents, Evaluating

Indeterminate Forms. Parametric Equations and Polar Coordinates: Parametrizations of Plane

Curves , Parametric Equations , Calculus With Parametric Curves:

Derivative,Length of Parametrically Defined Curve.

5

Polar Coordinates: Polar Equations , Relating Polar and Cartesian Coordinates, Graphing in Polar

Coordinates (line, circle, cardioid), Areas and Lengths in Polar Coordinates : Area in the Plane,

Length of a Polar Curve.

6

Vectors: Three-Dimensional Coordinate Systems, Vectors, The Dot Product, Angle Between

Two Vectors, Perpendicular Vectors, The Cross Product, Parallel Vectors. Lines and Line

Segments in Space: Vectors Equation for a Line, Parametric Equations for a

Line, An Equation for a Plane in Space, Lines of Intersection.Vector- Valued Functions:Curves in

Space and Their Tangents, Limits and Continuity, Derivatives,Velocity Vector,Acceleration

Vector,Differentiation Rules,Arc Length Along a Space Curve.

7

Functions of Several Variables: Domains and Ranges , Functions of Two Variables ,Graphs and

Level Curves of Functions of Two Variables,Functions of Three Variables, Level surfaces (plane,

sphere, cone, eliptic paraboloid, ellipsoid, cylinder), Limits for Functions of Two Variables,

Continuity, Two-Path Test for Nonexistence of a Limit , Continuity of Composites, Functions of

More Than Two Variables.

8 Midterm Exam

9 Partial Derivatives: Partial Derivatives of Fuctions of Two Variables, Partial Derivatives and

Continuity, Second Order Partial Derivatives, The Mixed Derivative Theorem, Partial Derivatives

of Still Higher Order, The Chain Rule: Chain Rule for Functions of Two Independent Variables,

Chain Rule for Functions of Three Independent Variables, Functions Defined on Surfaces, Chain

3

Rule for Two Independent Variables and Three Intermediate Variables

10

Implicit Differentiation Revisited. Directional Derivatives and Gradient Vectors : Directional

Derivatives in the Plane , Interpretation of the Directional Derivative , Calculation and

Gradients , Gradients and Tangents to Level Curves , Functions of Three Variables, Tangent

Planes and Differentials: Tangent Plane

of The Surface, The Normal Line of The Surface.

11

The Linearization of a Function of two Variables, Differentials . Extreme Values: Local

Extreme Values, First Derivative Test for Local Extreme Values, Critical Point, Saddle Point ,

Second Derivative Test for Local Extreme Values.

12

Quizz 1, Double Integrals : Double and Iterated Integrals over Rectangles, Double Integrals as

Volumes, Fubini’s Theorem (First Form), Double Integrals over General Regions , Double

Integrals over Bounded Nonrectangular Regions , Volumes (volumes

between two surfaces), Fubini’s Theorem (Stronger Form) .

13

Finding Limits of Integration :Using Vertical Cross-sections , Using Horizontal Cross-sections ,

Properties of Double Integrals, Area by Double Integration, Average Value Theorem, Double

Integrals in Polar Form: Finding Limits of Integration, Changing Cartesian

Integrals into Polar Integrals.

14Calculating volumes by using polar coordinates (volume between two surfaces), Substitutions in

Double Integrals.

15 Final Exam

RECOMMENDED SOURCES

-1.Thomas’ Calculus, 12th Edition, G.B Thomas, M.D.Weir, J.Hass and F.R.Giordano, Addison-Wesley, 2012.-2.Calculus: A Complete Course, Robert A. Adams,C Essex 7th Edition,AddisonWesley Longman Toronto 2010.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

4

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 10 3 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav

Kısa Sınav

Yarıyıl Sonu Sınavı





Course Learning

Outcomes


0

5

CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x xCLO5 x x x

6


Course Information

Year ofCurriculum


2Computer Programming II







Prerequisites None


Instructors

Assistants


Develop computer code with functions, analyze algorithms or computer code for correctness, use parameter passing methods, use pointers and strings effectively, know the relationship between pointers and arrays, analyze user-defined types (classes), develop computer code with classes.

Course Content

Functions, recursive functions, void functions, arguments by value, default arguments to a function, function overloading, arrays, 2-D arrays,pointers, arguments by reference, accessing arrays with pointers, passingarrays to functions, strings, accessing strings with pointers, classes, dynamic memory management, operatör overloading.



Learning Outcomes

1. Ability to develop computer code with functions

2. Ability to use parameter passing methods.

3. Ability to develop computer code using arrays, strings and pointers.

1

4. To understand relationships between strings, arrays and pointers.

5. To understand the use of classes and access control to class members.

6. Ability to develop basic computer code with classes/objects

7. Ability to create the user-defined types.

COURSE CONTENT

Week Topics

1 The form of a function and function parameters.

2 Argument passing by value.

3 Local, global variables.

4 Passing parameters by reference.

5 Default arguments

6 Arrays and passing arrays to functions.

7 Pointers and pointer arithmetic.

8 Midterm Exam. 1.

9 Strings, and accessing arrays and strings with pointers.

10 Introduction to classes.

11 Friend functions and friend classes.

12 Dynamic memory management.

13 Operator overloading.

14 recursive function calls.

15 Final Exam

RECOMMENDED SOURCES

C++ for Everyone, Second Edition, Cay Horstmann, Wiley, 2010.

Programming with C++, J. R. Hubbard, Schaum’s Outline Series, McGraw Hill, 1996.

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework

Attendance

Practice

Seminar

Practice

Internship of the Course 1 10

2

Project

Field Survey

Workshop 1 10

Laboratory

Presentation 1 50

Final examination

Total 3 40



Total 1 30

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework 5 5 25

Seminar

Presentation

Practice

Laboratory 15 2 30


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 15 15

Quizzes







Course Learning

Outcomes


0CLO1 x x x

3

CLO2 x x xCLO3 x x xCLO4 x x xCLO5 x x xCLO6 x x x xCLO7 x x x

4


Course Information

Year ofCurriculum


1 Management for Engineers







Prerequisites None


Instructors

Assistants


The objective of this course is to enable students to acquire a body of knowledge of the design, analysis, decision making, planning, process improvement and control as the main functions of engineering management and develop skills to determine performance measures and evaluate performance in engineering systems.

Course Content

Engineering management and scopeElements of engineering management: design, analysis, planning and control, process improvement and decision makingOrganizational design and technologyPerformance analysis and evaluationImprovement of quality and productivity.



Learning Outcomes

1. Define engineering management and give the scope of engineering management.

2. Explain the fundamental concepts and functions of engineering management.

1

3. Do the organizational design and use technology for organizational design

4. Explain the elements of performance analysis and evaluation

5. Determine performace measures in engineering systems and evaluate performance of systems

COURSE CONTENT

Week Topics

1 Engineering management, fundamental concepts and functions

2 Design of engineering systems

3 Analysis of engineering systems

4 Planning and control in engineering systems

5 Planning and control in engineering systems

6 Process improvement in engineering systems

7 Decision making in engineering systems

8 Development of a strategic plan

9 Midterm exam

10 Organizational design and technology

11 Performance analysis and evaluation in engineering systems



14 Quality and productivity in engineering systems

15 Final Exam

RECOMMENDED SOURCES

Chang, C.M. (2005). Engineering Management: Challenges in the New Millenium, 1st ed. Pearson Prentice Hall.

Eisner, H. (2008). Essentials of Project and Systems Engineering Management. 3rd ed., John Wiley &Sons.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Practice

2

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


2 15 30


Homework

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes

Homework(s)/Seminar(s)

Final examination 1 20 20

Total Work Load 30


ECTS Credit of the Course 2

3


Course Learning

Outcomes


0CLO1 x x xCLO2 xCLO3 xCLO4 x xCLO5 x x x

4


Course Information

Year ofCurriculum


2 Principles of Atatürk and History of Modern Turkey I







Prerequisites


Instructors

Assistants


To inform students about essential political, economic, social and cultural facts of the historical period from the late eighteenth century through the signing of Lausanne Treaty in 1923; in other words, to inform them about the background of these facts in the course of the transition from the Ottoman Empire to the establishment of republican Turkey. To provide students with some examples of a multi-layered point in order to make them able to approach historical events in a multi-dimensional way. To introduce to students certain basic theoretical concepts, discussions and methods of thought of different social sciences, with a particular emphasis on history.

Course Content

Basic political, economic, social and cultural facts of the historical period beginning by the classical age of the Ottoman Empire and ending by the signing of Lausanne Treaty in 1923 - the fundamental academic interpretations on them.

Teaching-Learning

1

Methods and Techniques Used in the Course


8 MIDTERM

9 The Era of Second Constitutional Monarchy: Pluralism in the Public Sphere

10 The First World War: “Total War” and the rise of the nationalism

11The General Social and Political Situation in the world and in the Ottoman State after the First World War

12 The War of Independence I: The Political Developments

13 The War of Independence I: The Military Developments

14 The Tanzimat Era (1839-1876): The Reconstruction of the centralized state

15 Final Exam

RECOMMENDED SOURCES

25-41 Eric Jan Zürcher, “Giriş: Dönemleme, Kuram ve Yöntem”, Modernleşen Türkiye’nin Tarihi içinde, s. 11-20 Eric Jan Zürcher, “Onsekizinci Yüzyıl Sonunda Osmanlı İmparatorluğu”, Modernleşen Türkiye’nin Tarihi içinde,s 23-38 Niyazi Berkes, “İç ve Dış Engeller”, Türkiye’de Çağdaşlaşma içinde,s. 65-80 Peter Burke, Tarih ve Toplumsal Kuram, s. 129-137 Eric Jan Zürcher, “Gelenek ve Bid’at Arasında”, Modernleşen Türkiye’nin Tarihi içinde, s. 39-77 Şerif Mardin, “Tanzimat Fermanı’nın Manası”, Türkiye’de Toplum ve Siyaset içinde, İstanbul: İletişim Yayınları, s. 288-310. İlber Ortaylı, “Osmanlı Tarihinde Bab-ı Ali Asrı”, İmparatorluğun en Uzun Yüzyılı içinde, s. 77-107 Eric Jan Zürcher,“1873-1878 Bunalımı ve Sonuçları” ve “Gerici İstibdat ya da Islahatların Doruğu ? Sultan II. Abdülhamit Saltanatı”, Modernleşen Türkiye’nin Tarihi içinde, s. 109-136 Eric Jan Zürcher, “İkinci Meşrutiyet Dönemi”, Modernleşen Türkiye’nin Tarihi içinde,s. 139-186 Zafer Toprak, “Milli İktisat”, Tanzimat’tan Cumhuriyet’e Ansiklopedisiiçinde, s. 740-747. Eric Jan Zürcher, “İdeolojik Tartışmalar”, Modernleşen Türkiye’nin Tarihi içinde, s.186-193 Gökçen-Faruk Alpkaya, “I. Dünya Savaşı”,20. Yüzyıl Dünya ve Türkiye Tarihi içinde, s. 71-79. Eric Jan Zürcher, “Bağımsızlık Savaşı”, Modernleşen Türkiye’nin Tarihi içinde, s 194-196 Toktamış Ateş, “Savaş Dönemi”, Türk Devrim Tarihiiçinde, s. 71-159 Taner Timur, “Milli Kurtuluş Savaşı”, Türk Devrimi ve Sonrası içinde, Ankara: İmge Yayınevi, s.13-61. Ahmet Mumcu, ‘Kurtuluş Savaşı’nın Bitişi (Mudanya Ateşkes Antlaşması / Saltanatın Kaldırılması /Lozan Antlaşması), Atatürk İlkeleri ve İnkılâp Tarihi Iiçinde, Eskişehir: Açıköğretim Fak. Yay., s. 212-233.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation

2


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


Sınıf Dışı Ders Çalışma Süresi (Ön çalışma, pekiştirme)

Ödev

Seminer

Sunum

Uygulama

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3

BOLOGNA DERS İÇERİK FORMU

DERS BİLGİLERİ

MüfredatYılı

Ders Adı Kodu Yarıyıl T+U Saat Kredi AKTS

2 Differential

Equations


Dersin Dili Türkçe

Dersin Düzeyi Lisans

Bölümü/Programı Bilgisayar Mühendisliği Lisans Bölümü

Öğrenim Türü Örgün Eğitim

Dersin Türü Zorunlu

Ön Koşul Dersleri

Bölüm/ProgramKoordinatörü

Dersin Sorumlusu (ları)

Dersin Yardımcıları

Dersin AmacıDevelop mathematical thinking and mathematics, physics and engineering to solve problems encountered in.

Dersin İçeriği Differential Equations, The Definition and Classification, Order and Degree of Differential Equations, Solutions of Differential Equations: The Integral Curve, İmplicit-Explicit Solution, Particular Solution, The General Solution, Singular Solution, İnitial Value Problem. Derivation of Differential Equations. First Order Differantial equations: SeparableDifferential Equations, Variables that can be converted Separable Differential Equations Differential Equations, Homogeneous Functions, Homogeneous Differential Equations, Becomes homogeneous differential equations that can be converted. Linear Equations, Method of Integrating Factors, Method of Variation Parameters, Bernoulli Equations, Exact Equations and Integrating Factors , Exact Equtions, The Method of İntegrating Factors Based ona Single Variable, Riccati Equations. First Order Higher Degree Differential Equations: Clairaut and Lagrange's Equations. Higher Order Linear Equations: Homogeneous Equations with Constant Coefficients, Characteristic Equation, Fundamental Solutions of Linear Homogeneous Equations, Linear independence and Wronskian Determinant, Complex Roots of The Characteristic

1

Equation, Real Valued Solutions, Repeated Roots, Reduction of Order.

Nonhomogeneous Equations Method of Undetermined Coefficients, Method of

Variation Parameters. Euler Differential Equation with Variable Coefficients. Some Special Second Order Equations: Equations with the Dependent Variable Missing, Equations with the Independent Variable Missing. Series Solutions of Second Order Linear Equations:Review of Power Series, Series Solutions Near an Ordinary Point. The Laplace Transform: The Laplace Transform, Definition of LaplaceTransform. The Inverse Laplace Transform, Definition of Inverse Laplace Transform. Solution of Initial Value Problems with the help of the Laplace Transformation. Systems of Linear Equation First Order Differential Equation:Elimination and Determinant Method

Derste Kullanılan Öğretme-Öğrenme Yöntem ve Teknikleri

Dersin Staj Durumu

Dersin Öğrenme Çıktıları

Students will learn to develop mathematical thinking.

Students will learn to gain ability of solving differential equations

Students will learn mathematics, physics and engineering to solve problems encountered in

Students will learn a method to be used to gain scientific research

Students will learn to solve many mathematical problems by establishing a differential equation model.

DERS AKIŞI

Hafta Konular

1

Differential Equations, The Definition and Classification, Order and Degree of Differential Equations,Solutions of Differential Equations: The Integral Curve, İmplicit-Explicit Solution, Particular Solution, The General Solution, Singular Solution, İnitial Value Problem.Derivation of Differential Equations.

2

First order Differantial equations: Separable Differential Equations, Variables that can be converted Separable Differential Equations Differential Equations, Homogeneous Functions, Homogeneous Differential Equations, Becomes homogeneous differentialequations that can be converted.

3Linear Equations, Method of Integrating Factors, Method ofVariation Parameters.

4Bernoulli Equations, Exact Equtions,The Method of İntegratingFactors Based on a Single Variable.

5 Riccati Equations. First-Order Higher-Order Differential Equations:

2

Clairaut and Lagrange's Equations.

6

Higher Order Linear Equations: Homogeneous Equations with Constant Coefficients,Characteristic Equation, Fundamental Solutions of Linear Homogeneous Equations, Linear independence and Wronskian Determinant. Complex Roots of The Characteristic Equation, Real Roots, Repeated Roots, NonhomogeneousEquations.

7 Method of Undetermined Coefficients

8 Midterm

9Method of Variation Parameters.Euler Differential Equation withVariable Coefficients

10Some Special Second Order Equations Equations: Equations with the Dependent Variable Missing, Equations with the IndependentVariable Missing.

11Series Solutions of Second Order Linear Equations: Review ofPower Series, Series Solutions Near an Ordinary Point.

12Midterm 2. The Laplace Transform: Definition of Laplace Transformand properties.

13The Inverse Laplace Transform, Solution of Linear Dif. Equationswith Constant Coefficients by Laplace Transformation

14Systems of Linear Equation First Order Differential Equation:Elimination and determinant method..

15 Final

KAYNAKLAR

- Elementary Differential Equations and Boundary Value Problems. William E. Boyce and

Richard C.DiPrima, Eighth Edition,2005,U.S.A.

- Diferansiel Denklemler.Cilt 1. Prof. Yavuz Aksoy . Yildiz Teknik Üniversitesi Fen Edebiyat

Fakültesi, Matematik Bölümü .YTÜ Yayınları. İstanbul

- Diferansiyel Denklemler.Cilt 2. Prof. Yavuz Aksoy, Yrd. Doç. Dr. E. Mehmet Özkan. Yildiz

Teknik Üniversitesi Fen Edebiyat Fakültesi, Matematik Bölümü

.YTÜ Yayınları. İstanbul

- Diferansiyel Denklemler . Prof.Dr. Mustafa Bayram . Yildiz Teknik Üniversitesi

Fen Edebiyat Fakültesi, Matematik Bölümü . 2011. İstanbul

DEĞERLENDİRME SİSTEMİ

YARIYIL İÇİ ÇALIŞMALARI SAYISI KATKI YÜZDESİ

Ara Sınav 1 40

Kısa Sınav

Ödev

Devam

Seminer

Uygulama


3

Proje

Arazi Çalışması


Laboratuvar

Sunum

Yarıyıl Sonu Sınavı 1 60

Toplam2 100

Yarıyıl İçi Çalışmalarının Başarı Notuna Katkısı 1 40

Yarıyıl Sonu Sınavının Başarı Notuna Katkısı 1 60

Toplam 2 100

AKTS / İŞ YÜKÜ TABLOSU

Etkinlik SAYISISüresi(Saat)

Toplamİş Yükü(Saat)



Ödev 5 5 25

Seminer

Sunum

Uygulama

Laboratuvar


Proje 1 20 20

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





DERSİN ÖĞRENME ÇIKTILARININ PROGRAM ÇIKTILARI İLE İLİŞKİLENDİRİLMESİ

Öğrenme Çıktıları PÇ1 PÇ2 PÇ3 PÇ4 PÇ5 PÇ6 PÇ7 PÇ8 PÇ9 PÇ10ÖÇ1. x x xÖÇ2. x x xÖÇ3. x x x xÖÇ4. x x xÖÇ5. X X X x

4


Course Information

Year ofCurriculum


2 Data Structures andAlgorithms Design

BMB303 Güz 4+2 6 8






Prerequisites None


Instructors

Assistants

Objectives of the CourseThe aim of the course is to provide students how to select and design data structures and algorithms that are appropriate for problems that they might encounter.

Course Content

1.Fundamentals of Algorithmic Problem Solving 2. Fundamentals of the Analysis of Algorithm Efficiency 3. List, Queue, Stack, Tree, Graph Data Structures and their applications 4. Searching Algorithms 5. Sorting Algorithms



Learning Outcomes

1. Student will understand how to design correct and efficient algorithms.

2. Student will learn major elementary data structures including stacks, queues, trees, graphs and should be able to use them appropriately to solve problems.

3. Student will learn a variety of techniques for designing algorithms.

4. Student will able to analyze worst-case, best-case and average case running times of algorithms

1

using asymptotic analysis.

5. Student will able to apply prior knowledge of standard algorithms to solve new problems.

COURSE CONTENT

Week Topics

1 Fundamentals of Algorithmic Problem Solving 1

2 Fundamentals of Algorithmic Problem Solving 2

3 Fundamentals of the Analysis of Algorithm Efficiency

4 Lists and Linked Lists

5 Queues and Stacks

6 Tree Structures

7 Binary Trees

8 Midterm Exam

9 Search Algorithms, String Search Algorithms

10 Sorting Algorithms

11 Recursion

12 Divide and Conquer Algorithms

13 Graph Algorithms (Shortest Path, Critical Path)

14 Graph Algorithms

15 Final Exam

RECOMMENDED SOURCES

Introduction to Algorithms, Third Edition, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, The MIT Press, 200Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne, Addison-Wesley Professional, 2011

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework 3 20

Attendance

Seminar

Practice


2

Project 1 10

Field Survey

Workshop

Laboratory

Presentation


Total 6 100



Total 6 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 6 90


Homework 3 10 30

Seminar

Presentation

Practice

Laboratory 10 7 70


Project 1 20 20

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


Total Work Load 31 73 240




Course Learning

Outcomes


0CLO1 x x x x x x xCLO2 x x x x xCLO3 x x x x x

3

CLO4 x x x xCLO5 x x x x x

4


Course Information

Year ofCurriculum


2 Web and Internet Technologies

BMB304 Güz 3+2 5 5






Prerequisites None


Instructors

Assistants


The aim of this course is to provide the basics of information about; editors used for web programming, programming languages used for development and editing, installation of web servers, web protocols, database connections and query on web environment.

Course Content

Editors and program development environments used for programming; Pagedesign with HTML5; the use of style sheets (CSS) for formatting; creating dynamic pages (javascript); web server setup; Cookie concept and usage areasin internet programming; sending HTTP requests and responses over the internet; connecting to the database via the internet and performing transactions; listing, sorting, changing the information in the database; developing a dynamic internet application for educational purposes.



Learning Outcomes

1. Knows the editors and programming languages used for web programming.

2. Develops a web page with HTML5 and format the web page with CSS.

3. Develops dynamic web pages with Javascript language.

1

4. Knows and use HTTP and other web protocols.

5. Knows how to connect to a database on the web and query it.

6. Develops an educational web application.

COURSE CONTENT

Week Topics

1 Course Introduction - Web Programming Editors and Web Programming Languages

2 Basic HTML5 Tags - List Tags - Ordered, Unordered, and Nested List Tags

3 Working with HTML5 Tables - Table Tags - Link Labels - Link Lists

4 Working with HTML5 Images, Sounds and Videos - Image Tags - Audio Tags - Video Tags

5Working with Forms - Form Labels - Text Fields - Password Fields - Multiple Selection Fields - Multiple Choice Fields - Buttons - New Form Elements in HTML5

6 Formatting Web Pages with CSS - Working with Colors - Formatting Text

7 CSS3 Selectors - Working with Class and Style - Working with div and Span - CSS3 Innovations

8 Midterm Exam

9Working with CSS3 Borders and Backgrounds - Borders and Features - Background Images and Formatting with CSS3 - Using Images in Lists

10CSS3 Levels - Managing Style Levels - Style Priorities – Browser Compliance Management - CSS Custom Effects - Image, Text, Transition, and Transformation Effects

11CSS3 Levels - Managing Style Levels - Style Priorities – Browser Compliance Management - CSS Custom Effects - Image, Text, Transition, and Transformation Effects

12JavaScript Conditional Expressions - Loops - Arrays - Working with Objects - Working with Canvas

13Programming Client Side with JavaScript - Writing Functions and Events - Button and Text Field Events

14 Working with the Database - Making a Database Query

15 Final Exam

RECOMMENDED SOURCES

- Harris, A., (2011), HTML, XHTML, &CSS, All-in-One. John Wiley & Sons.- McFedries, P., (2018), Web Coding- Harris, A., (2014), HTML5 and CSS3 All-in-One. John Wiley

ASSESSMENT


Mid-terms 1 40

Quizzes

2

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 5 75


Homework 5 5 25

Seminar

Presentation

Practice

Laboratory 5 6 30


Project 1 5 5

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 5 5

Quizzes





3


Course Learning

Outcomes


0CLO1 x x xCLO2 x xCLO3 x x xCLO4 x x xCLO5 x x xCLO6 x x

4


Course Information

Year ofCurriculum


2 Fundamentals of Electrical Networks







Prerequisites


Instructors

Assistants


Students will be able to identify basic concepts and principles of circuit analysis. Introducing the resistor, as a linear circuit component, along with dependent and independent sources, provide the students with anopportunity to learn a number of

very powerful engineering circuit analysis techniques.

Course Content

The course introduces concepts of circuits accompanied by detailed discussions of Ohm’s law and Kirchhoff’s laws. This is followed by circuit analysis techniques by using nodal and mesh analysis with a detailed discussion of what constitutes a linear electric circuit. The course starts with the topic of resistive circuits and then develops a number of very powerful engineering circuit analysis techniques, such as nodal analysis, mesh analysis, superposition, source transformation, and Thévenin’s and Norton’s theorems. After the resistive circuit analysis, the students are introduced to the operationalamplifier or op-amp for short, finds daily usage in a large variety of electronic applications. It also provides us a new element to use

in building circuits and analysis of circuits using this element.

1



Learning Outcomes

Identify basic circuit elements in electrical networks.

Apply engineering-oriented analysis of linear circuits.

Analyze the state equations of electrical circuits and their response to DC excitation.

Develop basic problem-solving skills to situations an engineer is likely to encounter.

COURSE CONTENT

Week Topics

1 Introduction

2Basic concepts: Unit Systems and Fundamental Definitions of

Electricity Terms.

3 Basic Components and Electric Circuits.

4 Voltage and Current Laws.

5 Voltage and Current Laws.

6Basic Nodal and Mesh Analysis. Power and Energy in Electric

Circuits.

7 Basic Nodal and Mesh Analysis.

8 Ara Sınav

9 Handy Circuit Analysis Techniques

10Superposition: Determining the Individual Contributions of Different

Sources.

11 Thevenin’s Theorem and Numerical Examples.

12 Norton’s Theorem and Numerical Examples.

13 The Operational Amplifier

14 The Operational Amplifier

15 Final Sınavı

RECOMMENDED SOURCES

-Engineering circuit analysis, 8th Edition, William H. Hayt, Jr., Jack E. Kemmerly, Steven M. Durbin, McGraw-Hill Education, 2012.-Basic Engineering Circuit Analysis, 8th Edition, J.D. Irwin, R. M. Nelms, Wiley, 2005.

2

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 5 25

Seminer

Sunum

Uygulama

Laboratuvar


Proje 1 20 20

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav


3





Course Learning

Outcomes



4


Course Information

Year ofCurriculum


2 Occupational English

BMB306 Güz 2+0 2 2






Prerequisites


Instructors

Assistants



Course Content




Learning Outcomes

Students learn technical phrases’ English, encountered during training.

Students will have the ability to derive meaning to read English documents.

1

Students will write simple English technical documentation of income level.

Students learn the differences between social English and technical English.

Students learn how to use technical terms, making presentations in English.

COURSE CONTENT

Week Topics

1 General information about translation techniques

2 Translation of documents in the field of Computer Sciences






8 Midterm Exam







15 Final Exam

RECOMMENDED SOURCES

Documents used in the field of Computer Sciences

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev

Seminer

Sunum

Uygulama

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x xCLO5 x x x x

3


Course Information

Year ofCurriculum


2 Principles of Atatürk and History of Modern Turkey I







Prerequisites


Instructors

Assistants


To inform students about essential political, economic, social and cultural facts of the historical period from the late eighteenth century through the signing of Lausanne Treaty in 1923; in other words, to inform them about the background of these facts in the course of the transition from the Ottoman Empire to the establishment of republican Turkey. To provide students with some examples of a multi-layered point in order to make them able to approach historical events in a multi-dimensional way. To introduce to students certain basic theoretical concepts, discussions and methods of thought of different social sciences, with a particular emphasis on history.

Course Content

Basic political, economic, social and cultural facts of the historical period beginning from 1923 to the present; fundamental academic interpretations on them.



1

(If there is)

Learning Outcomes

The students will acquire a perspective to evaluate the 20.th century.

The students will evaluate the political, economic and cultural policies of the early republican era.

The students will evaluate the political, economic and cultural policies of the Democratic Party era.

The students will evaluate the political, economic and cultural policies after the military coup of 1980.

The students will evaluate today within the context of Republican history.

COURSE CONTENT

Week Topics

1 An overview of the 20th century

2 Political Life between 1923-1945

3 The formation of the Republican Ideology and the Kemalist Principles

4 The Social and Cultural Transformation between 1923-1950

5 The Turkish Economy between 1923-1945

6 International Relations of Turkey between 1923-1945

7 The Passage of Turkey to the plural political system: 1945-1950

8 MİDTERM

9 1950-1960: Political Developments During the Years of Democratic Party

10 Politics in Turkey between 1960-1980

11 Economic Development and Social change in Turkey between 1960-1980

12 The Military Intervention in 1980 and the Rise of the Neo-Liberalism

13 Gender Politics in Turkey

14 The Constitutions in Turkey

15 Final Exam

RECOMMENDED SOURCES

25-41 Eric Jan Zürcher, “Giriş: Dönemleme, Kuram ve Yöntem”, Modernleşen Türkiye’nin Tarihi içinde, s. 11-20 Eric Jan Zürcher, “Onsekizinci Yüzyıl Sonunda Osmanlı İmparatorluğu”, Modernleşen Türkiye’nin Tarihi içinde,s 23-38 Niyazi Berkes, “İç ve Dış Engeller”, Türkiye’de Çağdaşlaşma içinde,s. 65-80 Peter Burke, Tarih ve Toplumsal Kuram, s. 129-137 Eric Jan Zürcher, “Gelenek ve Bid’at Arasında”, Modernleşen Türkiye’nin Tarihi içinde, s. 39-77 Şerif Mardin, “Tanzimat Fermanı’nın Manası”, Türkiye’de Toplum ve Siyaset içinde, İstanbul: İletişim Yayınları, s. 288-310. İlber Ortaylı, “Osmanlı Tarihinde Bab-ı Ali Asrı”, İmparatorluğun en Uzun Yüzyılı içinde, s. 77-107 Eric Jan Zürcher,“1873-1878 Bunalımı ve Sonuçları” ve “Gerici İstibdat ya da Islahatların Doruğu ? Sultan II. Abdülhamit Saltanatı”, Modernleşen Türkiye’nin Tarihi içinde, s. 109-136 Eric Jan Zürcher, “İkinci Meşrutiyet Dönemi”, Modernleşen Türkiye’nin Tarihi içinde,

2

s. 139-186 Zafer Toprak, “Milli İktisat”, Tanzimat’tan Cumhuriyet’e Ansiklopedisiiçinde, s. 740-747. Eric Jan Zürcher, “İdeolojik Tartışmalar”, Modernleşen Türkiye’nin Tarihi içinde, s.186-193 Gökçen-Faruk Alpkaya, “I. Dünya Savaşı”,20. Yüzyıl Dünya ve Türkiye Tarihi içinde, s. 71-79. Eric Jan Zürcher, “Bağımsızlık Savaşı”, Modernleşen Türkiye’nin Tarihi içinde, s 194-196 Toktamış Ateş, “Savaş Dönemi”, Türk Devrim Tarihiiçinde, s. 71-159 Taner Timur, “Milli Kurtuluş Savaşı”, Türk Devrimi ve Sonrası içinde, Ankara: İmge Yayınevi, s.13-61. Ahmet Mumcu, ‘Kurtuluş Savaşı’nın Bitişi (Mudanya Ateşkes Antlaşması / Saltanatın Kaldırılması /Lozan Antlaşması), Atatürk İlkeleri ve İnkılâp Tarihi Iiçinde, Eskişehir: Açıköğretim Fak. Yay., s. 212-233.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev

Seminer

Sunum

Uygulama

Laboratuvar


Proje

3

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



4


Course Information

Year ofCurriculum


2 Discrete Mathematics


Language of Instruction Türkçe

Course Level Lisans

Department/Program Bilgisayar Mühendisliği Lisans Programı

Education Type Örgün Öğrenim

Course Type Zorunlu

Prerequisites


Instructors

Assistants


Course ContentTo learn a particular set of mathematical facts and how to apply them and how to think mathematically.


Logic; Sets and Functions; Fundamentals of Algorithms; Integers and matrices; Counting Techniques; Chromatics Polinomials; Graphs; Trees; Boolean Algebra; Finite-State Machine with/without Output


Learning Outcomes

1. The student will learn the basics of creating a mathematical model.

2. The student will learn mathematical concepts and terminology.

3. The student will know how to analyze recursive definitions, and how to use it.

4. The student will understand how to use different types of discrete structures.

5. The student will know how to perform mathematical proofs.

COURSE CONTENT

1

Week Topics

1 The Language of Mathematics

2 Logic, Sets and Functions-I

3 Logic, Sets and Functions-II

4 Algorithms and Complexity of Algorithms

5 Counting Techniques

6 Relations-I

7 Choromatic Polinomials

8 Midterm Exam

9 Trees and their Applications-I

10 Trees and their Applications-II

11 Graph Theory-I

12 Graph Theory-II

13 Midterm Exam

14 Finite State Machine with/without output

15 Final Exam

RECOMMENDED SOURCES

- Discrete Mathematics and Its Applications, Kenneth H. Rosen, McGraw-Hill- Discrete Mathematics, R. Johnsonbaugh, Prentice Hall- Discrete Mathematics, Kenneth A. Ross, Prentice Hall

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework

Attendance 1 10

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation

2


Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 3 45


Homework 6 5 30

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 5 5

Quizzes


Total Work Load 90




Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x xCLO4 x x xCLO5 x x x

3


Course Information

Year ofCurriculum


2 Introduction to Electronic







Prerequisites


Instructors

Assistants


The aim of this course is to provide department operations,

departments, related student clubs and department introduction;

to teach ethical principles and engineering definitions to students;

to provide information on subjects such as entrepreneurship and

project management.

Course Content

The first part is: Occupational information: General information about

electronics and communication engineering, the field of study of

electronic and communication engineering, general knowledge about

electronics and technology, professional ethics and principles in daily

life, occupational law, entrepreneurship, project and presentation

preparation techniques, electronic and communication circuits and

standards in their definition. Second part: Electrical quantities and

units, introduction to electric circuits, resistances, series-parallel

network structures, capacitors, measurement methods and

measuring devices, direct current- alternating current concepts,

linear-nonlinear circuits, systematic identification, modeling and

optimization concepts

Teaching-Learning

1

Methods and Techniques Used in the Course


Learning Outcomes

The students learn knowledge about the basic concepts of Electronics and Communications

Engineering.

The students gain knowledge on importance of Electronics in technology and in daily life.

Students learn about electrical circuits, measurement techniques and measuring devices.

Students take the first step in designing electronic circuitry with teamwork.

The students learn about the project preparation and presentation techniques.

COURSE CONTENT

Week Topics

1What is Electronics and Communication Engineering? What are the

working areas?

2

What are the ethics and principles of profession? Information on the effects of

engineering applications on health, environment and

safety in universal and social dimensions

3

Gaining information about the standards used in engineering applications, Knowledge

about applications in business, such as project management, risk management and

change management,

Awareness about the legal consequences of engineering solutions.

4 Basic concepts and units of electrical quantities

5 Introduction to electric circuits

6 Resistance, capacity, inductance elements

7 Resistance, capacity, inductance elements

8 Midterm Exam

9 Kirschoff's laws, Series, parallel circuits

2

10 Electrical measuring instruments and measurements

11 Discrete signal, continuous signai, direct current, alternative current

12 Linear and nonlinear circuits

13 Introduction to communication

14 Project and Presentation Preparation Techniques

15 Final Exam

RECOMMENDED SOURCES

- John Bird, “Electrical and Electronic Principles and Technology” Newnes, 2001

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

3

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



4


Course Information

Year ofCurriculum


3 Operating System







Prerequisites None


Instructors

Assistants


Basic architecture of operating systems, hardware and software requirements andapplication areas of operating systems.

Course Content

- Basic architecture of operating systems, hardware and softwarerequirements and

- application areas of operating systems.Teaching-Learning Methods and Techniques Used in the Course


Learning Outcomes

1. Students will be able to distinguish different styles of operating system design.

2. Students will understand device and I/O management functions in operating systems as part of a uniform device abstraction.

3. Students will understand the main principles and techniques used to implement processes and threads as well as the different algorithms for process scheduling.

4. Students will understand the main mechanisms used for inter-process communication.

1

5. Students will understand the main problems related to concurrency and the different synchronization mechanisms available.

6. Students will be able to give the rationale for virtual memory abstractions in operating systems.

COURSE CONTENT

Week Topics

1 History of operating systems and introduction to operating systems

2 Hardware requirements of operating systems

3 Processes and process management mechanisms

4 Basic process scheduling algorithms and their comparison

5 Interprocess communication

6 Memory management, real and virtual memory

7 Mechanisms for creating virtual memory

8 Midterm Exam

9 Paging and segmentation in memory management

10 I/O systems and memory hierarchy

11Basic principles of the operation of I/O systems, sequential and

random access techniques

12Sharing of I/O systems between user processes and virtual I/O

systems-Basic file system structure for operating systems

13 Midterm Exam

14Logical file system and its mapping to physical I/O, sharing and

security concerns

15 Final Exam

RECOMMENDED SOURCES

-Operating Systems, Internals and Design Principles, W. Stallings, Pearson - Prentice Hall-Operating System Concepts, Abraham Silberschatz, Peter Baer Galvin, Addison- Wesley-Learning the UNIX Operating System, Fifth Edition, O'Reilly Media

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

2

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework 5 5 25

Seminar

Presentation

Practice

Laboratory 8 5 40


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes






Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x x xCLO4 x x

3

CLO5 x x xCLO6 x x

4


Course Information

Year ofCurriculum


2Probability and Statistics BMB405 Spring 3 3 4






Prerequisites None


Instructors

Assistants

Objectives of the CourseThe aim of the course is to give some basic terms and concepts in Probability & Statistic, and teach how / why to be used the statistics methods and probability theory in engineering.

Course Content

Basic concepts and rules of probability / Random variables: Disrict and Continuous / Expected value and variance, covariance / Bivariate marginal and conditional distributions / The popular distributions / Sampling and descriptive statistics / Introduction to estimation theory / Interval estimation / Test of hypotheses / Simple linear regression and correlation


Lecture and Project


Learning Outcomes

1-The students will be able to use the basic principles of descriptive statistics

2-The students will be able to calculate simple probabilities and also outcomes from random variables

3-The students will be able to carry out and/ or check statistical surveys

4-The students will be able to use the terminology in the framework for this course

1

COURSE CONTENT

Week Topics

1Introduction to Probability and statistics, history, interdisciplinary phenomena, the general application areas

2Arrangement of the data (simple, frequency and class series, the cumulative-modulating frequencies, graphs)

3Central Tendency Measures (Arithmetic, Mode, Median ...), Measures of Variability (Range, Standart Deviation, Variance), Measures of Shape(Kurtios, Skewness, Variance), Asymmetry Measures

4Probability (sample space, event, axioms, set theory, counting, permutations, combinations) şartsal probability, Bayes' theorem)

5 Random Variables (Discrete random variables)

6 Random Variables (Continuous random variables)

7 Discrete Probability Distributions (Bernoulli, Binomial, Geometric, Hypergeometric, Poisson)

8 Midterm

9 Continuous Probability Distributions (Gamma, Beta, Normal)

10Estimation theory 1 (Estimation and estimation methods, and the rate of population mean interval estimation)

11Estimation theory 2 (differencef of means, and proportions, between the population variance of the interval estimate)

12Tests of Hypothesis 2 (the difference between the means, the difference between the proportions)

13Tests of Hypothesis 2 (the difference between the means, the difference between the proportions)

14Simple Regression and Correlation 1 (parameter estimation, coefficient of determination, regression model)

15 Final

RECOMMENDED SOURCES

Probability and Statistics in Engineering, William W. Hines, Douglas C. Montgomery, David M. Goldsman, Connie M. Borror, Wiley, 2003. 2- Probability and Statistics for Engineering and the Sciences, Jay L. Devore, Duxbury Press, 2011.

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework

Attendance

Practice

Seminar

Practice


2

Project 1 30

Field Survey

Workshop

Laboratory

Presentation 1 40

Final examination

Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework

Seminar

Presentation

Practice

Laboratory


Project 3 10 30

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes







Course Learning

Outcomes


0CLO1 x x x

3

CLO2 x x xCLO3 x x xCLO4 x x x

4


Course Information

Year ofCurriculum


2 Database Management







Prerequisites None


Instructors

Assistants

Objectives of the CourseUnderstanding database modeling, querying, and management techniques.

Course Content

Conceptual Design with ER/UML Modelling; Relational Model; Relational Algebra; SQL; DB Integrity Programming Techniques (Assertions, Triggers); DB-driven Programming Languages (Stored Procedures, Embedded SQL, JDBC); Semi-structured Modelling; XML; XML Programming Languages (XPath, XQuery)



Learning Outcomes

1. The student is able to design and model medium-scale databases.

2. The Student is able to criticize the database design issues and how to write basic SQL queries.

3. The student is able to use database management tools in the laboratory environment.

4. The student is able to design and program database-driven programs.

5. The student is able to apply new generation DB modelling/programming languages such asXML, Xquery and XPath

1

COURSE CONTENT

Week Topics

1Introduction to fundementals of database concepts and main

architecture of db systems.

2 DB conceptual desgin with ER

3 DB conceptual desgin with EER and UML

4 Relational Model, RM Design

5 Relational Algebra

6 SQL

7 SQL, SQL Programming

8 Midterm

9 SQL Programming (Stored Procedures, Embedded SQL, JDBC)

10 database integrity (triggers), security

11 semistructure data models: XML

12 XML, XPath

13 XPath, XQuery programmig

14 New generation Database Systems (NoSQL)

15 Final Exam

RECOMMENDED SOURCES

- Elmasri, Navathe, Fundementals of Database Systems, Addison Wesley, 2010- Veri tabanı Sistemleri, Ünal Yarımağan, Akademi Kitapevi

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

2

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 5 75


Homework 6 5 30

Seminar

Presentation

Practice 5 10 50

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 1 10

Quizzes






Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x xCLO4 x x x

3

CLO5 x x x

4


Course Information

Year ofCurriculum


2 Logic CircuitsBMB407 Spring 2+1 3 4






Prerequisites None


Instructors

Assistants

Objectives of the CourseThe objective of this course, to give knowledge about principles of logic circuits and combinational and sequential logic analysis and design.

Course Content

Overview of Digital Systems / Number Systems and Conversion / BooleanAlgebra / Algebraic Simplification of Boolean Functions / Applications of Boolean Algebra, Logic Gates / Karnaugh Maps / Quine-McCluskey Method / Multi-level logic gate circuits, NAND and NOR gates / Multiple Output Logic Circuits / Multiplexers / Decoders / Encoders / Read-Only Memory (ROM), Programmable Logic Gate Arrays (PAL) / Combinational Logic Circuit Design / Sequential Logic Circuits Overview / Latches and Flip-Flop Circuits / Registers and Counters / Sequential Logic Circuits Analysis / Derivation of State Diagrams and Tables / Reduction of State Tables and Assignment / Sequential Logic Circuit Design / Logic Circuit Design with Data Flow Method.


Lecture, Project and Homework


Learning Outcomes

1-Learns the number systems, codes and conversion used in digital systems.

2-Learns the Boole Algebra, Boole Functions and Algebraic Simplification.

1

3-Learns the applications of Boole Algebra and Logic Gates.

4-Learns the Karnugh Maps and Quin-McCluskey Table simplification methods.

5-Gains the knowledge on the multi-level logic gate circuits and multi-output logic circuits.

6-Learns the Decoder, Coder and Multiplexer Circuits.

7-Learns design of the combinational logic circuits.

8-Gains the knowledge on the Programmable Combinational and Sequential Logic Circuits.

9-Learns the analysis and design of sequential logic circuits.

10-Learns the digital logic circuits design, analysis and simulation using electronic design automation software.

COURSE CONTENT

Week Topics

1 Overview of Digital Systems and Number Systems and Conversion

2 Boolean Algebra, Algebraic Simplification of Boolean Functions

3 Applications of Boolean Algebra, Logic Gates, Karnaugh Maps

4 Karnaugh Maps, Quine-McCluskey Method

5 Combinational Logic Adders, Subtractors

6 Multiplexers, Decoders, Encoders

7 Read-Only Memory (ROM), Programmable Logic Gate Arrays (PAL)

8 Midterm

9 Sequential Logic Circuits Overview, Latches and Flip-Flop Circuits

10 Sequential Logic Circuits Analysis

11Sequential Logic Circuits Analysis, Derivation of State Diagrams and Tables, Reduction of State Tables and Assignment

12 Sequential Logic Circuit Design

13 Registers and Counters

14 Logic Circuit Design with Data Flow Method

15 Final

RECOMMENDED SOURCES

Fundamentals of Logic Design, 5th Edition by Charles H. Roth, Jr., 2004 Logic and Computer Design Fundamentals, 3rd Edition by M. Morris Mano and Charles R. Kime, Published by Prentice-Hall, 2004.

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework 1 10

2

Attendance

Practice

Seminar

Practice


Project 1 10

Field Survey

Workshop

Laboratory

Presentation 1 50

Final examination

Total 4 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework 1 1 10

Seminar

Presentation

Practice

Laboratory


Project 1 1 10

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 1 20

Quizzes



Total Work Load 19 27 4.00



3


Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x xCLO4 x x xCLO5 x x xCLO6 x x x xCLO7 x x xCLO8 x x x x xCLO9 x x xCLO10 x x x x x

4


Course Information

Year ofCurriculum


2 Intership I BMB408 Spring 0 0 1






Prerequisites None


Instructors

Assistants

Objectives of the CourseThe purpose of the internship is improve the practical works of student inthe academical area.

Course Content

Internship jobs in any public or private sector, six weeks (30 working days) requires the acquisition of professional experience. Students who successfully complete the internship are required to follow the rules of the Department of Computer Engineering Internship directive.



Learning Outcomes

1. The student will apply the acquired theoretical knowledge in practice.

2. The student will establish a relationship with the future colleagues who work in the IT field.

3. The student will assess the student’s ability to apply discipline-related knowledge to the field.

4. The student will learn to present the information acquired in an official report.

5. The student will learn to take responsibilities and learn to work with different groups.

1

COURSE CONTENT

Week Topics

1 Professional Experience




5

6

7

8

9

10

11

12

13

14

15

RECOMMENDED SOURCES

ASSESSMENT


Mid-terms

Quizzes

Homework 1 20

Attendance

Seminar

Practice


Project 1 20

2

Field Survey

Workshop

Laboratory

Presentation 1 60

Final examination

Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Homework

Seminar

Presentation

Practice

Laboratory


Project 1 1 30

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms

Quizzes

Final examination





Course Learning

Outcomes


0CLO1 x x xCLO2 x xCLO3 x x xCLO4 x x

3


Course Information

Year ofCurriculum


3 Introduction Computer Network







Prerequisites None


Instructors

Assistants


Design and application protocols and applications in computer

communication networks

will be studied. A conclusion that successfully completes the course will

learn the network layers and the different protocols at the layer.

Course Content

Overview of computer networks. Network structure and OSI model.

Network topology, link analysis, delay analysis, backbone analysis.

Physical layer, communication and multiplexing, terminal, errors. Link

layer and link protocols. Network layer, routing and congestion, satellite

and packet radio networks, local networks. Communication layer,

presentation and application layers.


Lecture and Lab


Learning Outcomes

1- To understand the computer network architecture

1

2. To comprehend and compare different transmission devices used for communication purposes.

3. To be able to detect the errors that may occur during transmission or to understand the correction techniques

4. To be able to comprehend the different routing protocols used in communication networks

5. To comprehend communication techniques in shared spaces, such as in wireless networks

6. To understand how the Internet, Ethernet and ATM networks work

7- Collecting and analyzing data over the Internet using Wireshark

COURSE CONTENT

Week Topics

1Computer Networks and the Internet

2Computer Networks and the Internet

3 Application Layer

4 Application Layer

5Transmission Layer

6Transmission Layer

7Transmission Layer

8Midterm Exam

9Network Layer

10Network Layer

11Network Layer

12Network Layer

13Link Layer

14Link Layer

15 Final examination

RECOMMENDED SOURCES

Computer Networking A Top-Down Approach, Sixth Edition by James F. Kurose and Keith W. Ross, Pearson, 2013

2

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Practice

Seminar

Practice


Project

Field Survey

Workshop

Laboratory 1 20

Presentation


Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 3 45


Homework 5 5 25

Seminar

Presentation

Practice

Laboratory 5 10 50


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


3


Total Work Load 150

Total Work Load / 30 (h) 5.00

ECTS Credit of the Course 5.00


Öğrenme

Çıktıları

PÇ1 PÇ2 PÇ3 PÇ4 PÇ5 PÇ6 PÇ7 PÇ8 PÇ9 PÇ10

ÖÇ1. xÖÇ2. x XÖÇ3. XÖÇ4. xÖÇ5. XÖÇ6. XÖÇ7. x

4


Course Information

Year ofCurriculum


3 Microprocessor BMB502 Autumn 2+2 4 5






Prerequisites None


Instructors

Assistants

Objectives of the CourseTheory and applications on Intel microprocessors, peripheral devices and memoryorganizations.

Course Content

Intel 8086 and 286 Architecture; Input-Output Device; 8255 PPI; 8251 USART; 8254 PIT; ADC and DAC; Interrupt Requests; 8259 PIC; Memory Organizations;Address Decoding



Learning Outcomes

1. The ability of designing conceptual microprocessor systems and developing target based software

2. Ability to apply basic sciences in the field of computer engineering.

3. Understending the concept of microprocessor architecture and programming.

4. Ability to design hardware microprocessor systems to meet desired needs.

5. Ability to create algorithmic solutions to inspect, improve and enhance existing systems by means of analytical approaches.

1

6. Ability to use techniques and modern engineering tools necessary for engineering practice.

7. Ability to function as a member of a team (from lab).

COURSE CONTENT

Week Topics

1 Intel 8086 and 286 Architecture and Structure

2 Input-Output Device Programming

3 8255 PPI - Programmable Parallel Interface - Mod 0 - 4x4 Keypad

4 8255 PPI - Mod 1 - Mod 2

5 8251 USART

6 8251 USART Applications

7 8254 Peripheral Interval Timer(PIT)

8 8254 PIT – Frequency Meter Application

9 Subroutine, interrupt and stack concept

10 ADC and DAC Applications

11 Interrupt Requests

12 8259 and Interrupt Requests

13 Midterm Examination 2

14 Memory Organizations - SRAM, DRAM, EPROM - AddressDecoding

15 Samples of fundemantal application

RECOMMENDED SOURCES

- The Intel Microprocessors 8086/8088, 80186/80188, 80286, 80386, 80486, Pentium, and Pentium Pro Processors Architecture, Programming and Interfacing- Barry B.Brey, Prentice Hall, 8. Baskı, 2008.-x86 PC: Assembly Language, Design and Interfacing, Muhammad Ali Mazidi vd., 5. baskı, Prentice Hall, 2010.-Mikroislemcilere Giris: Assembler ile Yazılım ve Arayüz, Mehmet Bodur,TMMOB EMO, 2016.- Mikroislemcilere Giris: Assembler ile Yazılım ve Arayüz, Mehmet Bodur,TMMOB EMO, 2016.

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework

Attendance

Practice

Seminar

2

Practice


Project 1 30

Field Survey

Workshop

Laboratory

Presentation 1 40

Final examination

Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework

Seminar

Presentation

Practice

Laboratory


Project 11 5 55

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 15 15

Quizzes


Total Work Load 150




Course Learning

Outcomes


0

3

CLO1 x x xCLO2 x x x x xCLO3 x x xCLO4 x x x xCLO5 x xCLO6 x x xCLO7 x x

4


Course Information

Year ofCurriculum


3Computer Architecture BMB503 Autumn 3+1 4 5






Prerequisites None


Instructors

Assistants

Objectives of the CourseMain objective of this course is to cover properties of various computer architectures and give new techniques in computer architecture to improve system performance.

Course Content

Computer System, Coputer Evolution and Performance, Central Processing Unit Design, Cache, Cache Optimization, Virtual Memory, Instruction-Level Parallelism, Pipeline, Data-Level Parallelism, GPU Architectures, Thread-Level Parallelism, Multicore Processors


Lecture and Homework


Learning Outcomes

1-Technical competence in computer architecture and high performance computing

2-Ability to describe the operation of modern and high performance computers

3-Ability to undertake performance comparisions of modern and high performance computers

4-Understand the several advanced optimizations to achieve cache performance

5-Technical competence in computer architecture and high performance computing

1

COURSE CONTENT

Week Topics

1 Introduction and Computer System

2 Coputer Evolution and Performance

3 Central Processing Unit Design

4 Cache

5 Cache Optimization

6 Virtual Memory

7 Instruction-Level Parallelism

8 Midterm 1

9 Data-Level Parallelism I

10 Data-Level Parallelism II

11 GPU Architectures

12 Thread-Level Parallelism

13 Multicore Processors

14 Presentations

15 Final

RECOMMENDED SOURCES

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework 1 30

Attendance

Practice

Seminar

Practice


2

Project

Field Survey

Workshop

Laboratory

Presentation 1 40

Final examination

Total



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework 12 5 60

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


Total Work Load 150




Course Learning

Outcomes


0CLO1 x x x x x x xCLO2 x x x xCLO3 x x x x x

3

CLO4 x xCLO5 x x x x x

4


Course Information

Year ofCurriculum


3 Automata Theory







Prerequisites


Instructors

Assistants


To improve programming language skills by achieving basic

knowledge of classification and definition of languages, and

relation to automata and their functions.

Course Content

Alphabet, Language, Grammar, Classification of Grammars,

Chomsky Hiearchy, Regular Grammars, Context Free Grammars,

CFG and BNF, Parse Tree, Left Recursion and Elimination, Pumping

Dilemma, Decision Problem, Normal Forms, Pushdown Automata,

Context Sensitive Grammars, Linear Bounded Automata,

Unrestricted Grammars, Turing Machine, Curch Turing Hipotesis.



Learning Outcomes

1. Students improve their language learning skills.

1

2. Students will earn motivations to learn new programming languages.

3. Students will learn automata and types.

4. Students will learn the limitations of the codes generated by grammars.

5. Students will be able to differentiate the grammars that can be used as programming languages.

COURSE CONTENT

Week Topics

1 Course Introduction and Basic Terms

2 Grammars And Chomsky Hierarchy

3 Regular Grammars

4 Context Free Grammars, Parse Trees

5 CFG Notation

6 BNF Notation

7 Left Recursion and Elimination, Pumping Dilemma

8 Midterm Exam

9 Decision Problem, Normal Forms, Pushdown Automata

10 Context Sensitive Grammars, Linear Bounded Automata

11 Unrestricted Grammars, Turing Machines

12 Turing Machines

13 Church-Turing Hypothesis

14 Review

15 Final Exam

RECOMMENDED SOURCES

-John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman “Introduction to Automata Theory,

Languages, and Computation 2E.”, Addison Wesley

2

- Harrison, M.A.: Introduction to Formal Language Theory. Addison–Wesley

- Ü. Yarımağan, "Özdevinirler (Otomatlar) Kuramı ve Biçimsel Diller, 2. Baskı", Seckin

Yayinevi

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

3

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



4


Course Information

Year ofCurriculum


3 Object Oriented Programming I







Prerequisites


Instructors

Assistants


To gain the ability of making good and proper object-oriented

modeling, design and implementation according to commonly agreed

principles

Course Content Gang of Four design patterns, code smells, refactoring



Learning Outcomes

1. Students will be able to identify the smells in object oriented code.

2. Students will be able to carry out object oriented analysis and design tasks on real world problems.

3. Students will be able to use the classical Gang-of-four patterns during object oriented analysis and design.

4. Students will be able to refactor object oriented code.

5. Students will be able to carry out object oriented design tasks on real world problems.

1

COURSE CONTENT

Week Topics

1 Introduction to design patterns, MVC pattern

2 Patterns for creating objects without explicit usage of their classes

3Patterns for reducing the dependency on the implementation of anobject

4 Patterns for reducing algorithmic dependency

5 Patterns for obtaining loose coupling

6 Patterns for object aggregation

7 Patterns for easier modification of classes

8 1st Midterm exam

9 Utility patterns

10 Selected code smells and refactoring operations to remove them



13A demonstation of refactoring operations on a complete codeexample

14 Presentation and discussion of project works

15 Final Exam

RECOMMENDED SOURCES

Refactoring: Improving the Design of Existing Code, Martin Fowler. Addison- Wesley, 1999Design Patterns – Elements of Reusable OO Software, Erich Gamma et.al(Gang of Four), Addison-Wesley, 1994

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


3 Web Design and Programming







Prerequisites


Instructors

Assistants

Objectives of the CourseTo know web publishing principles. To have skills of web content

developing.

Course Content

Fundamentals and functions of the Internet. Common Internet

applications used in education: e.g., WWW, e-mail, chat, ftp, etc.

Principles of using Internet applications in education.



Learning Outcomes

1. Students can understand and write basic HTML commands.

2. Students can understand and write basic CSS commands.

3. Students can understand and write basic JS commands.

4. Students can combine HTML, CSS and JS structures.

5. Students can design own web page at a very elemantary level.

1

COURSE CONTENT

Week Topics

1Introduction, General Information about the lecture, Introduction toWeb Programming

2 Introduction to HTML, Adding Picture and Web Link to Your Page

3 Common tags and styling fonts

4 Styles, Quotes and Colors in HTML

5 Some CSS Commands

6 ID, Class, Tables, Lists

7 Introduction to CSS

8 Midterm

9 Colors, Margins, Padding in CSS

10 Font Styling, Icons in CSS

11 Tables and Lists in CSS

12 Introducing to Javascript, Data Types in JS

13 Methods in JS

14 Animations and Effects

15 Final Exam

RECOMMENDED SOURCES

- Robbins, Jennifer Niederst. Learning web design: A beginner's guide to HTML, CSS, JavaScript, and web graphics. " O'Reilly Media, Inc.", 2012.- David Sawyer McFarland "JavaScript & jQuery: The Missing Manual", 2ndEdition, O'Reilly Media / Pogue Press 2011

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


3 Server Operating Systems







Prerequisites None


Instructors

Assistants


Operating Systems, History of operating systems, Process Concept:States & process control blocks, OS Kernel, Concurrent Processes, Mutualexclusion, Process Synchronization, Semaphores, Memory Management &Scheduling, Multiprogramming, Virtual Memory, Paging & Segmentation,On demand paging & segmentation, Operations on Moving Head Disks,Disk Scheduling Policies, File System Functions, Blocking and Buffering,File Organization.

Course Content

Operating Systems, History of operating systems, Process Concept:States & process control blocks, OS Kernel, Concurrent Processes, Mutualexclusion, Process Synchronization, Semaphores, Memory Management &Scheduling, Multiprogramming, Virtual Memory, Paging & Segmentation,On demand paging & segmentation, Operations on Moving Head Disks,Disk Scheduling Policies, File System Functions, Blocking and Buffering,File Organization.


Lecture and Lab


Class room discussion,

Learning Outcomes

1- İşletim sistemlerin içerikleri, role ve amaçlarının kavranması,

1

2- Programlama dili, işletim sistemi ve bilgisayar donanım nasıl birlikte çalıştığının kavranması,

3- İşletim sistemi önemli dizayn konularından verimli, hızlı ve esnek çalışma, birden fazla sisteme taşınabilirlilik, güvenlilik, uyumluluk, API interface, aygıt organizasyonları ve kullanıcı /sistem durum değişimi gibi kavramların bilinmesi,

4- Süreç içerigi, süreç durumu, karşılıklı dışlama, süreç senkronizasyonu, ve çoklu programlama promlemleri tanımak ve kavramak,

5- Durum diagramlari, hazır sırası, bekleme sırası ve calışma sırası, süreç kontrol blokları, süreç değiştirme, süreç kontrol blokları, ve sıralama politikaları anlaşılması,

6- Kısır döngüden kaçınma, tanınması, engellenmesi ve kurtarılması konularının bilinmesi ve bunlara çözümler geliştirilmesi semaforlar, şartlı değişkenler ve thread kullanarak.

7- Fiziksel bellek ve bellek yönetimleri, sayfalama ve parçalama, planlama politikaları anlamak,

COURSE CONTENT

Week Topics

1 An overview of operating systems and their functions

2 Computer hardware and operating system, microprocessor status, memory ordering

3 Process contents, process states, concurrent processes, process control blocks,

4 Thread contents, multi-core processors, mutual exclusion

5 Process sequences, Sorting algorithms, Process sequences

6 Memory management, introduction of important, real memory and virtual memory conceptsin multi-user systems

7 Methods used for using virtual memory and necessary hardware features

8 Midterm exam

9 Introduction of input-output systems and their place in memory hierarchy

10 Working principles of input-output systems, sequential and random access

11 Sharing input-output systems among users, introducing the concept of virtual input-output unit / File system, comparison of mesh systems with a flat and hierarchical structure

12 Examination of the relationship between the logical file system and physical peripherals andthe sharing and security needs in multi-user systems

13 Providing inter-process communication and synchronization, deadlock concept and solution methods

14 Examination and comparison of process operating methods

15 Final Sınavı

RECOMMENDED SOURCES

Abraham Silberschatz, Peter B. Galvin, Greg Gagne, Operating System Concepts. 8th edition. Addison-Wesley.

ASSESSMENT


Mid-terms 1 20

Quizzes

2

Homework 1 20

Attendance

Practice

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 5 75


Homework 3 5 15

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 20 20

Quizzes


Total Work Load 150


ECTS Credit of the Course 5.00

3


Course Learning

Outcomes


0CLO1 x x x xCLO2 x x x xCLO3 x x x xCLO4 x x xCLO5 x x xCLO6 x x x xCLO7 x x

4


Course Information

Year ofCurriculum


3 Sistem Programming







Prerequisites


Instructors

Assistants


Obtaining a general knowledge about the technologies used to

develop

web/Internet applications and to develop a team project.

Course Content

System Programming Concepts; 2-Tier, 3-Tier and N-Tier Application

Development Models; Client/Server Architectural Model; HTML; CSS;

Scripting; XML; XSLT; DTD; W3C-Schema; DOM; SAX; General

Structure of RPC-based Applications; General Structure of RMI-based

Applications; Web based Application

Development Tools, System Security;



Learning Outcomes

1. Knowledge on the differences between client-server and conventional applications.

2. Learns HTML , CSS and JavaScript technologies in order to develop web based applications.

1

3. Learns how to use XHTML and XML for electronic data transfer, XPath and XSLT for

document transformations, DTD and XSD used for validity purpose and DOM and SAX to edit

XML files.

4. Knows the general structure of RPC, RMI, and Web Services for distributed application

development.

5. Gain the ability to develop a Web-based application as a group work.

COURSE CONTENT

Week Topics

1 System programming concept

2 Client/Server based applications and their specifications

3 2-Tier, 3-Tier and Multi-Tier application specifications.

4 Web applications, HTML and CSS

5 Javascript and client side controls

6 XML, and DTD to validate XML documents

7 W3C Schema to validate XML documents

8 Ara Sınav

9 XPATH , XSLT Usage, Introduction to DOM and SAX

10 XPATH , XSLT Usage, Introduction to DOM and SAX

11 RPC and application development with RPC, RMI and application development with RMI

12Comparison of distributed application developmenttechnologiesRMI and application development with RMI

13 Student project presentations

14 Student project presentations

15 Final Exam

RECOMMENDED SOURCES

- Client/Server Survival Guide, Orfali,R., Harkey, D., Edwards, J.- Java.rmi: Remote Method Invocation Guide, Pitt, E, McNiff K.- Power Programming With RPC, Bloomer, J.- XML:How to Program, Deitel,H.M., Deitel, P.J., Neito, T.R., Lin, T.M., Sadhu, P.

Internet

2

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project 1 20

Field Survey

Workshop

Laboratory

Presentation


Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje 1 30 30

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav

3






Course Learning

Outcomes



4


Course Information

Year ofCurriculum


3 Algorithm Analysis and Design







Prerequisites


Instructors

Assistants


The goal of this course is to introduce advanced techniques for the

design and analysis of major classes of algorithms, and explores a

variety of applications.

Course Content

Fundamentals of the Analysis of Algorithm Efficiency, Asymptotic

Notations, Analysis of Divide and Conquer Algorithms, Hashing

Algorithms, Graph Algorithms, Balanced Search Trees, Dynamic

Programming, Backtracking, P, NP and NP-Complete Problems



Learning Outcomes

1. Students will be able to analyze the correctness of algorithms.

2. Students will learn the concepts of time and space complexity, worst case, average case

and best case complexities and asymptotic notations.

3. Students will be able to design efficient algorithms for major engineering problems.

1

4. Students can compute complexity measures of algorithms.

COURSE CONTENT

Week Topics

1 Fundamentals of the Analysis of Algorithms Efficiency

2 Asymptotic Analysis

3 Analysis of Nonrecursive and Recursive Algorithms

4 Analysis of Divide and Conquer Algorithms

5 Hashing Algorithms 1

6 Hashing Algorithms 2

7 Dynamic Programming 1

8 Midterm Exam 1

9 Dynamic Programming 2

10 Graph Algorithms

11 Balanced Search Trees (2-3 trees, B-trees, Red-Black trees)

12 Backtracking

13 Midterm Exam - 2

14 NP, NP-Complete, NP-hard Problems

15 Final exam

RECOMMENDED SOURCES

Introduction to the Design and Analysis of Algorithms (3rd Edition) by Anany Levitin, 2011The Algorithm Design Manual(2nd Edition), Steven S Skiena, 2010

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

2

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


3 Object Oriented Programming II







Prerequisites


Instructors

Assistants

Objectives of the Course To teach the Object-Orientation paradigm

Course Content

Object oriented programming concepts, Unified Modeling

Language(UML),Class design, Applets, Inheritance, Polymorphisim,

Interface and abstract classes, design patterns, frameworks, Application programming interfaces (API)



Learning Outcomes

1. Students gain to the ability of solving the real-world problems by using the object-oriented

paradigm and describe these solutions by using UML schemas.

2. Students have ability to make a presentation, which results in self-confidence.

3. Students learn to the base of Inheritance, Polymorphism, Encapsulation

1

4. Students have knowledge about the new generation software applications.

COURSE CONTENT

Week Topics

1Introduction to object oriented programing(OOP): Thinking objectbased,history and design

2Object oriented programing:properties, methods, events. Control structure, Loops and Arrays

3Object and Class design, UML (class diagrams, object diagramsand activity diagrams)

4 Interface and polymorphism

5 Pattern and GUI programming

6 Pattern and GUI programming (continue)

7 Inheritance and abstract classes

8 Exam

9 Java Object Model

10 Frameworks

11 Multithreading

12 Multithreading

13 Other design patterns

14 Project presentations

15 Final Exam

RECOMMENDED SOURCES

Cay Horstmann, "Object-Oriented Design and Patterns", 2nd Edition, 450 pages, Wiley, ISBN: 0-471-74487-5C# 2010 How to program, Deitel, Prentice Hall, 2010David D. Riley, “The Object of Java”, Addison Wesley,2002.David J. Barnes, “Object-Oriented Programming with Java”, Prentice Hall, 2000.John Lewis, William Loftus “Java Software Solutions”, Addison Wesley, 2003.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice

2


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes


0CLO1 x x xCLO2 x x x

3

CLO3 x x x xCLO4 x x xCLO5 x x x

4


Course Information

Year ofCurriculum


3Introdction Artificial İnteligence







Prerequisites None


Instructors

Assistants


Students will gain understanding on the basics of artifical intelligence.They will learn logic programming and how to apply it to problems relatedto artifical intelligence. They will solve problems coming from applicationareas related to artifical intelligence.

Course Content

Representation of knowledge. Search and heuristic programming. Logicand logic programming. Applications related to problem solving, gamesand puzzles, expert systems, planning, learning, vision, and naturallanguage understanding.


Lecture and Lab


In class lectures- Interactive problm solving- Coding exercises

Learning Outcomes

1 Students will know how to use game trees in computer games.

2 Students will know how to use motion algorithms in computer games.

3 Students will know how to use pathfinding algorithms in computer games.

4 Students will know how to use tactical and strategic artificial intelligence algorithms in computer games.

1

5 Students will know how to use learning and decision making algorithms in computer games.

COURSE CONTENT

Week Topics

1 Introduction, Game AI, Random Numbers

2 Kinematic Movement

3 Steering Behaviors

4 Pathfinding

5 Project Meeting

6 Decision Making I

7 Midterm

8 Ara Sınav

9 Tactical and Strategic AI

10 Learning I

11 Project Meeting

12 Board Games

13 Supporting Technologies


15 Final Sınavı

RECOMMENDED SOURCES

Artificial Intelligence for Games, Ian Millington and John Funge. Morgan Kaufmann, 2. Edition. ISBN 0123747317

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework

Attendance

Practice

Seminar

Practice


Project 1 30

Field Survey

Workshop

Laboratory

Presentation

2


Total



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 3 45


Homework

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 5 5

Quizzes


Total Work Load 90




Course Learning

Outcomes


0CLO1 x x x x x xCLO2 x x x xCLO3 x x x x xCLO4 xCLO5 x x x x

3


Course Information

Year ofCurriculum


2 Intership I BMB408 Spring 0 0 1






Prerequisites None


Instructors

Assistants

Objectives of the CourseThe purpose of the internship is improve the practical works of student inthe academical area.

Course Content

Internship jobs in any public or private sector, six weeks (30 working days) requires the acquisition of professional experience. Students who successfully complete the internship are required to follow the rules of the Department of Computer Engineering Internship directive.



Learning Outcomes

1. The student will apply the acquired theoretical knowledge in practice.

2. The student will establish a relationship with the future colleagues who work in the IT field.

3. The student will assess the student’s ability to apply discipline-related knowledge to the field.

4. The student will learn to present the information acquired in an official report.

5. The student will learn to take responsibilities and learn to work with different groups.

1

COURSE CONTENT

Week Topics





5

6

7

8

9

10

11

12

13

14

15

RECOMMENDED SOURCES

ASSESSMENT


Mid-terms

Quizzes

Homework 1 20

Attendance

Seminar

Practice


Project 1 20

2

Field Survey

Workshop

Laboratory

Presentation 1 60

Final examination

Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Homework

Seminar

Presentation

Practice

Laboratory


Project 1 1 30

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms

Quizzes

Final examination





Course Learning

Outcomes


0CLO1 x x xCLO2 x xCLO3 x x xCLO4 x x

3


Course Information

Year ofCurriculum


4 Occupational Health and Safety I

BMB701 Güz 2+0 2 2






Prerequisites None


Instructors

Assistants


The main purpose of the course is to introduce the risk factors having effects on occupational accidents and diseases, and to teach how to perform the evaluation of risks which have an important role on avoiding such situations. Simultaneously, to get involved in accidents and occupational diseases within the Department of Control and Automation Engineering, to inform about the Law on Occupational Health and Safety No. 6331 and as a result the participation of students in occupational health and safety and the creation of safe culture are also included in the aims of the course.

Course Content

Risk Management, Risk Evaluation, Risk Analysis, Risk Perception, Psychosocial Risk Factors, Physical Risk Factors, Ergonomic Risk Factors, Chemical Risk Factors, Risk Evaluation Methods, Risk Control Steps, Risk Evaluation Stages, Risk Evaluation Documentation, Risk Evaluation Application, Working on Tools with Screen, Ergonomic Work, Protection from Occupational Musculoskeletal diseases



Learning Outcomes

1. The student knows the concepts of danger, risk, near miss, event / case, accident and the

1

difference between them

2. The student learns why the risk assessment is performed, its function, who and how it is done

3. The student knows the psychosocial, biological, chemical, physical hazards and knows the principles of protection from these hazards

4. The student has an idea and can contribute to a healthier work environment

5. She detects the hazards earlier and can be more sensitive about the precautions

6. Know what to do or not in case of an accident or emergency

7. He may notice the risks that may be encountered in the faculty, and he or she has the ability to take precautions to keep them under control.

8. Adapt to occupational health and safety practices to be implemented in the faculty, awareness occurs

COURSE CONTENT

Week Topics

1Risk Management and Evaluation, Risk Management and General Management, Hazard and Risk Concepts, Risk Sources and Risks, Risk Assessment as a Part of Risk Management, Basic Principles of Risk Assessment

2Risk Assessment Methods, Qualitative Methods, Quantitative Methods, Fine-Kinney Method,L Type Matrix, X Type Matrix, Fta, Eta, Cca, Fmea, Jsa, Hazop, Pra, Pha

3Risk Assessment Methods, Qualitative Methods, Quantitative Methods, Fine-Kinney Method,L Type Matrix, X Type Matrix, Fta, Eta, Cca, Fmea, Jsa, Hazop, Pra, Pha

4Occupational Health and Safety in Working with Tools with Screen, Risks and Safeguards in Working with Tools with Screen, Correct Seating, Protection of Eyes, Eyes During Working Shortly, Resting Habit, Interrupted Rests and Exercises

5Ergonomics, Lesson Work Ergonomic Work Place Arrangement And Cautions, Office Ergonomics, Cognitive Ergonomics, Physical Ergonomics, Administrative Ergonomics, Anthropometry And Working Environment Design

6Psychosocial Risk Factors, Stress, Factors Causing Stress, Stress Stages, Stress Protection Methods, Effects of Work Stress on Health, Long Term Effects of Stress, Psychological Harassment (Mobbing) and Coping Methods

7Risk Communication, Risk Perception, Informing Employees, Taking Employee Opinions, Communication and Persuasion

8 Midterm Exam

9Physical Risk Factors, Noise, Vibration, Pressure, Lighting, Thermal Comfort (Working in Humidity, Hot or Cold, Heating and Ventilation), Radiation, Ionized Rays, Non-ionized Rays

10Chemical Risk Factors and Protection Methods, Protection Methods, Carcinogenic and Mutagenic Materials, Hazardous Area Classes

11Fire and Protection Methods, Safety in Fire, Classification and Extinguishing of Fire, Emergency Management, Preparation of Emergency Plans and Transfer to Employees, Measures and Exercises, First Aid and Emergency Response, Hazard Communication

12Occupational Health and Safety at University, Hazards in Classrooms, Hazards in Cafeteria and Cantiles, Psychosocial Hazards Biological Hazards, Chemical Hazards, Electrical Hazards

13Analysis of the statistics on occupational accidents and illnesses, the most frequent accidents and illnesses and precautions.

14 Risk analysis examples

15 Final Exam

2

RECOMMENDED SOURCES

Main Text and Regulations of the Law No. 6331 on Occupational Health and SafetyWorkplace Medicine and Job Security Specialist Course Notes

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 2 30


Homework

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

3

Quizzes


Total Work Load 17 60




Course Learning

Outcomes


0CLO1 xCLO2 x xCLO3 xCLO4 x xCLO5 xCLO6 x xCLO7 xCLO8 x x

4


Course Information

Year ofCurriculum


4 Project I BMB702 Autumn 3+1 4 8






Prerequisites None


Instructors

Assistants

Objectives of the CourseMake students to gain experience about hardware and software related subjects with projects that combine them.

Course ContentAbility to solve problems in public and global domains with the help of studied software and hardware topics.



Learning Outcomes

1. Students will learn the requirements of computer engineering, analytical thinking and approaching problems to produce algorithmic solutions.

2. Students will able to implement systems development life cycle in the projects.

3. Students will able to revise and improve systems designed by using the results obtained by implementing experiments and solutions.

4. Students will learn effectively writing of their team projects in reports.

5. Students will understand independent learning of new technologies and concepts in order to complete the project.

6. Students will learn how to interact professionally with others in the workplace, to engage effectively in teamwork.

1

COURSE CONTENT

Week Topics

1 Project topic research

2 Determination of the project topic

3 Evaluation of related works about the project topic

4 Preparation of the feasibility report

5 Determination of application details and modules

6 Database design

7 Implementation

8 Submission of the first progress report

9 First project consultation

10 Implementation

11 Implementation

12 Submission of the second progress report

13 Second project consultation

14 Implementation

15 Presentation of project

RECOMMENDED SOURCES

- Every kind of books, articles, research reports related to the project topic.

ASSESSMENT


Mid-terms

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation 2 60


Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework

Seminar

Presentation 3 20 60

Practice

Laboratory


Project 3 20 60

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


Total Work Load 240




Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x xCLO4 x x x xCLO5 x x xCLO6 x x x

3


Course Information

Year ofCurriculum


4 Artificial Learning and Artificial NeuralNetworks

BNB703 Autumn 2+1 3 5






Prerequisites


Instructors

Assistants

Objectives of the Course Learning basic problems and solution techniques in neural networks.

Course ContentLearning basic methods and applications used in neural networks.

Determining whether a method fits into the problem given.



Learning Outcomes

1. Students will be able to recognize the basic problems in the aera.

2. Students will be able to construct the suitable models for the problems

3. Students will be able to determine the proper solution for the models

4. Students will understand the limitations of available tools

5. Students will know how to interpret results

1

COURSE CONTENT

Week Topics

1 Why use neural networks ? Biological fondations of ANNs.

2 Application areas, typical architectures, activation functions

3 McCulloch-Pitts Neuron

4 Simple Neural Networks for Pattern Classification

5 Perceptron, Adaline, Delta Rule

6 Multilayer Perceptrons

7 Radial Based Networks

8 Midterm Exam

9 Gradient Descent, Backpropogation algorithms and variations

10 Regression Analysis

11 Learning Vector Quantization

12 Pattern Association, learning algorithms, associative networks

13 Pattern Association, learning algorithms, associative networks

14 Hopfield Networks

15 Final Exam

RECOMMENDED SOURCES

-Fundamentals of Neural Networks: Architectures, Algorithms and Applications, Laurene V. Fausett, Pearson; 1 edition (December 19, 1993)-Neural Network Design (2nd Edition) – Martin T Hagan

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


4 Decision Support Systems







Prerequisites


Instructors

Assistants


Builidng models involve to transform realworld problem to standard structure. Furtermore, companies collecting more data day by day. In that datawarehouse companies tries to find useful information. There are some computer based systems that simplifies the process. The aimof this course is to be familiar with this applications.

Course Content

vermelerinde yardımcı olan bilgisayar tabanlı bilgi sistemlere denir. Verileri ve modellerin etkin kullanımını sağlayarak karmasık problemlerin çözümüne katkıda bulunurlar.



Learning Outcomes

1. Student will get ability to use decision support systems

2. Student will get ability to investigate data structure

3. Student will gain the ability of how to implement real time applications

1

COURSE CONTENT

Week Topics

1 Introduction to course

2 The importance of decision making

3 The components of decision support systems

4 The functions of decision support systems

5 The benefits of decision support systems

6 The kinds of of decision support systems

7 The subjects of sample decision support systems in management and finance

8 The subjects of sample decision support systems in management and finance

9 Group decision support systems

10 Decision analysis instruments-1



13 Web based decision support systems for investigation decisions



RECOMMENDED SOURCES

Greenwood Publishing Group, 2002

Decision Support Systems: Concepts and Resources for Managers, Daniel J. Power

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


2

Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x x x

3


Course Information

Year ofCurriculum


4 Basics Deep Learning

Autumn 2+1 3 5






Prerequisites


Instructors

Assistants

Objectives of the CourseLearning and applying solution techniques using deep architectures on different application areas.

Course Content

History and therotical advanteges of the deep learning, basic learning algorithms and architectures for deep learning, regularization of distributed models, optimization techniques for training deep networks, convolutional networks, bacpropogating and recurrent networks, autoencoders and linear factor models, learning by demonstration, deep generative networks - Boltzman machines



Learning Outcomes

1. Students can evalute the deep learning techniques in terms of their effectiveness.

2. Students can evalute the advantages and disadvanteges of a specific deep learning technique.

3. Students can design and test basic deep learning solutions.

4. Students can determine and apply the appropriate deep learning architecture and

1

algorithm for the proposed solution.5. Students have knowledge on regularization and optimization techniques.

COURSE CONTENT

Week Topics

1 Introduction, history and basic theory

2 Mathematical background

3 Neural Networks

4 Feed forward deep networks

5 Regularization of deep and distributed models

6 Optimization techniques for training of deep models

7 Convolutional Networks

8 MidTerm Exam

9 Bacpropogating and recureent networks

10 Autoencoders and linear factor models

11 Learning by demonstration

12 Deep generative models -Boltzman Machines

13 Project Presentaions

14 Project Presentaions

15 Final Exam

RECOMMENDED SOURCES

-Yoshua Bengio, Ian J. Goodfellow and Aaron Courville, “ Deep Learning”, Book in preparation for MIT Press, http://www.iro.umontreal.ca/~bengioy/dlbook, 2015.-Yoshua Bengio, “Learning Deep Architectures for AI”, Foundations and Trends in Machine Learning: Vol. 2: No. 1, pp 1-127, 2009.-Li Deng and Dong Yu, "Deep Learning: Methods and Applications", Foundationsand Trends in Signal Processing: Vol. 7: No. 3–4, pp 197-387, 2014.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


2

Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3

CLO5 x x x

4


Course Information

Year ofCurriculum


4 Mobile Programming







Prerequisites


Instructors

Assistants

Objectives of the CourseTo teach mobile programming techniques and basics of mobile

technologies

Course Content

An Overview of Mobile Technologies ; Mobile Devices ; Mobile OS ;

Introduction to Mobile Application Development ; Mobile App

Components ; Application Lifecycle ; User Interface Design (Menus,

Dialog boxes, etc.) ; ListView ; ViewPager ; ArrayAdapters; Databases

on Smartphones and Data Management ; Sensors on Smartphones

and Sensor Data Collection ; Broadcast Receivers ; Notifications,

User Rights and Permissions ; Location-based Services ; Background

Tasks



Learning Outcomes

1. Students will design, develop and test a mobile application taking the smartphone restrictions into account.

1

2. Students will learn the (dis)advantages of each mobile development methods.

3. Students will follow up-to-date progress on mobile technologies.

4. Students will learn in-situ (on-premise) processing techniques.

5. Students will able to upload his/her mobile application into app market.

COURSE CONTENT

Week Topics

1 An Overview of Mobile Technologies

2 Mobile Devices and Mobile Operating Systems

3 Mobile Application Development Methods and Environments

4Introduction to Mobile Application Development / Mobile App

Components / Application Lifecycle

5 User Interface Design (Menus, Dialog boxes, etc.)

6 RecyclerView / ViewPager / ArrayAdapters

7 Databases on Smartphones and Data Management

8 MidTerm Exam

9 Sensors on Smartphones and Sensor Data Collection

10 Broadcast Receivers

11 Content Providers

12 Notifications, User Rights and Permissions

13 Location-based Services and Maps

14 Background Tasks

15 Final Exam

RECOMMENDED SOURCES

- Bill Phillips, Brian Hardy, “Android Programming: The Big Nerd Ranch Guide (Big Nerd Ranch Guides)”, 2013

- Jeff McWherter, Scott Gowell,” Professional Mobile Application Development, John Wileyhttp://developer.android.com

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

2

http://developer.android.com/

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


4 Introduction to Python Programming







Prerequisites


Instructors

Assistants

Objectives of the Course Learn to use statistical software programming in Python

Course Content

Python Programming Language; Python Data Types; Python Data

Input; Regression Applications with Python; Discrete Variables

and Statistical Tests;

Logit with Python; Bayesian Statistics with Python; Applications



Learning Outcomes

1 Get to know Python Software

2 Learn to data input and structure

3 Learn to write software about statistics with Pyhton

4 To develop information to solve statistical problems with Python

5 Analyse the real world applications of data with Python

1

6.

7.

8.

COURSE CONTENT

Week Topics

1 Introduction to Python Programming

2 Data Structures in Python

3 Data input and visualization in Python

4 Statistical Distribution in Python

5 Hypothesis in Python

6 Linear Regression in Python

7 Ara Sınav 1

8 Multivariate Data Analysis with Python

9 Tests for discrete data in Python

10 Bootstrap with Python

11 Logistic regression with Python

12 Bayesian Statistics in Python

13 Applications with Python

14 Linear Regression in Python

15 Final Exam

RECOMMENDED SOURCES

- “An Introduction to Statistics with Python”, Thomas Halswater, Springer-Verlag, 2016.- Think Stats 2e Allen B. Downey- Classnotes

ASSESSMENT


Mid-terms 1 40

2

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





3


Course Learning

Outcomes



4


Course Information

Year ofCurriculum


4 Autumn 2+1 3 5






Prerequisites


Instructors

Assistants


To gain the ability to apply basic mathematical operations and advanced mathematics in Matlab, develop the ability to program in Matlab by teaching basic programming logic and concepts, to gain the ability to create and edit graphics in Matlab

Course Content

Phrases, Operations, Arrays (Vector, Matrix and Polynomials), Programming,Function Programming, Conditional Expressions, Loops, Graphics in Matlab.



Learning Outcomes

1. Students will be able to do basic mathematical operations in Matlab.

2. Students will be able to transfer mathematical topics such as vectors, polynomials and matrices to Matlab.

3. Students will be able to define the basic concepts of programming.

4. Students will be able to write basic and complex programs in Matlab with writing, function, conditional expression and loop.

1

5. Students will be able to create graphs in Matlab.

COURSE CONTENT

Week Topics

1 Introduction to the course.

2 Introduction to Matlab. Phrases and Operations in Matlab.

3 Arrays in Matlab (Vector, Matrix and Polynomials)

4 Arrays in Matlab (Vector, Matrix and Polynomials)

5 Introduction to Programming / Quiz 1

6 Programming in Matlab

7 Programming in Matlab

8 Midterm 1

9 Conditional Expressions in Matlab

10 Conditional Expressions in Matlab

11 Loops in Matlab

12 Loops in Matlab / Quiz 2

13 Graphics in Matlab

14 Graphics in Matlab

15 Final Exam

RECOMMENDED SOURCES

- "Matlab Kılavuzu”, Doç. Dr. Aslan İnan“Matlab - Uygulama & Çözümleri”, Doç. Dr. Aslan İnan

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

2

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


4 Human andComputerInteraction







Prerequisites


Instructors

Assistants

Objectives of the CourseThe objective of this course is to have students get basic information and skills for human-computer interaction studies.

Course Content

Basic concepts in human-computer interaction; history of human-computer interaction; philosophy of human-computer interaction; cognitive aspects of human being and information processing theory; mental models, psychology and human- computer interaction; technologies used in human-computer interaction; design approaches;usability, effectiveness and efficiency; interface evaluation methods; usability testing.



Learning Outcomes

1. To know basic concepts of human-computer interaction

2. To know design approaches for technology design

1

3. To know evaluation methods used in human-computer interaction

4. To plan, apply, and evaluate a usability test

5. To know the relationship between human-computer interaction and the other fields of study

COURSE CONTENT

Week Topics

1 Introduction to the course Basic concepts of human-computer interaction

2History of human-computer interaction Philosophy of human-computer interaction

3Cognitive aspects of human being and information processingtheory

4 Mental models, psychology and human-computer interaction

5 Accessibility

6 Design approaches

7 Usability, effectiveness and efficiency

8 User experience

9 Midterm exam

10Technologies used in human-computer interaction; designapproaches

11Evaluation methods used in human-computer interaction Interfaceevaluation methods Usability testing




15 Final Research Paper and Presentation

RECOMMENDED SOURCES

- Kürşat Çağıltay. 2018. Teoriden Pratiğe İnsan – Bilgisayar Etkileşimi ve Kullanılabilirlik Mühendisliği. Seçkin Yayınları.- Kerem Rızvanoğlu. 2009. Herkes İçin Web Evrensel Kullanılabilirlik ve Tasarım. Punto Yayınları.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

2

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






3

Course Learning

Outcomes



4


Course Information

Year ofCurriculum


4 Occupational Health and Safety I







Prerequisites None


Instructors

Assistants


The main aim of the course is to educate the students about occupationalhealth and safety, to get involved in accidents and occupational diseases within the Department of Electronics and Communication Engineering, to inform about the Law on Occupational Health and Safety No. 6331 and asa result the participation of students in occupational health and safety and the creation of safe culture.

Course Content

Basic Rights and Obligations, Occupational Health and Safety Law No. 6331, Obligations of Employers, Employee Responsibilities, Employee Participation and Informing, OHSAS / TS 18001, Occupational Health and Safety Policy, Occupational Accidents and Occupational Diseases Prevention, Occupational Health and Safety Culture Health and Safety Signs, Health and Safety Education and Communication at Work, Nationaland International Organizations and Contracts, Occupational Health and Safety Committees, Occupational Health and Safety Services, EmergencyManagement, Risk Management and Evaluation, Health and Safety Management System, Basic First Aid Information, Occupational Health and Safety in Education



1

Learning Outcomes

1. Student has knowledge about Occupations and occupational diseases

2. Learn legal rights and responsibilities in occupational health and safety

3. Has knowledge about the Law No. 6331 on Occupational Health and Safety and its applications

4. Know the duties and responsibilities of the occupational safety specialist and the occupational physician, the work of the occupational health and safety body, and the importance of risk assessment

5. It plays an active role in creating a Job Safety Culture by creating safe behaviors and habits

6. Know what to do or not in case of an accident or emergency

7. He may notice the risks that may be encountered in the faculty, and he or she has the ability to take precautions to keep them under control

8. Adapt to occupational health and safety practices to be implemented in the faculty, awareness occurs

9. Having the necessary knowledge to create a healthier and safer environment in the faculty

COURSE CONTENT

Week Topics

1Concepts and Rules of Occupational Health and Safety, Occupational Health and Safety in Turkey and in the World, Historical Development of Occupational Health and Safety in Turkey and in the World. Contemporary business health and safety principles

2

Occupational health and safety culture, Behavior oriented management, Lifelong learning inoccupational health and safety, Integrated approach to occupational health and safety, Occupational health and safety in business management, Risk prevention culture at workplace, Safety culture prominence and place in everyday life, and continuation

3Constitution law, statute, regulation, communiqué, circular and directive concepts. Law No. 6331 on Occupational Health and Safety, Employers' obligations, Employee obligations

4Definition and general concepts of Occupational Health and Safety Law No. 6331, hazard, risk, risk assessment proactive approach, reactive approach, prevention, work accident, support staff, employee, employee representative

5Occupational Health and Safety Services, Occupational Safety and Health Specialist, Occupational Health and Safety, Occupational Health and Safety Unit, Common Health and Safety Unit, Registered Notebook

6The duties, powers and responsibilities of contemporary approaches to occupational health and safety, occupational safety specialist, workplace physician, other health personnel, employee representative

7Risk prevention principles, Priority ordering in health and safety, Prevention practices in thesource, Protection applications for the environment, Protection applications for the person

8 Midterm Exam

9TS 18001 Occupational Health and Safety Management System, Management system components, Occupational health and safety policy, PUKO cycle

10Chemical Risk Factors and Protection Methods, Protection Methods, Carcinogenic and Mutagenic Materials, Hazardous Area Classes

11 Occupational health and safety board, occupational health and safety council

12 Health Surveillance and Occupational Diseases, Health surveillance concept and its

2

application, Occupational disease concept, Occupational disease types and causes, Occupational diseases protection

13

Occupational health and safety education and communication, Characteristics and techniques of adult education, Qualifications and period of education, Occupational health and safety and vocational education of employees, Basic concepts about effective communication process in workplace

14 Risk analysis examples

15 Final Exam

RECOMMENDED SOURCES

Main Text and Regulations of the Law No. 6331 on Occupational Health and SafetyWorkplace Medicine and Job Security Specialist Course Notes

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 2 30


Homework

Seminar

Presentation

3

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


Total Work Load 17 60




Course Learning

Outcomes


0CLO1 xCLO2 x xCLO3 xCLO4 x xCLO5 xCLO6 x xCLO7 xCLO8 x xCLO9 x x

4


Course Information

Year ofCurriculum


4 Project II BMB802 Spring 3+1 4 8






Prerequisites None


Instructors

Assistants

Objectives of the CourseMake students to gain experience about hardware and software related subjects with projects that combine them.

Course ContentAbility to solve problems in public and global domains with the help of studied software and hardware topics.



Learning Outcomes

1. Students will learn the requirements of computer engineering, analytical thinking and approaching problems to produce algorithmic solutions.

2. Students will able to implement systems development life cycle in the projects.

3. Students will able to revise and improve systems designed by using the results obtained by implementing experiments and solutions.

4. Students will learn effectively writing of their team projects in reports.

5. Students will understand independent learning of new technologies and concepts in order to complete the project.

6. Students will learn how to interact professionally with others in the workplace, to engage effectively in teamwork.

1

COURSE CONTENT

Week Topics

1 Project topic research

2 Determination of the project topic

3 Evaluation of related works about the project topic

4 Preparation of the feasibility report

5 Determination of application details and modules

6 Database design

7 Implementation

8 Submission of the first progress report

9 First project consultation

10 Implementation

11 Implementation

12 Submission of the second progress report

13 Second project consultation

14 Implementation

15 Presentation of project

RECOMMENDED SOURCES

- Every kind of books, articles, research reports related to the project topic.

ASSESSMENT


Mid-terms

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation 2 60


Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework

Seminar

Presentation 3 20 60

Practice

Laboratory


Project 3 20 60

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


Total Work Load 240




Course Learning

Outcomes


0CLO1 x x xCLO2 x x xCLO3 x x xCLO4 x x x xCLO5 x x xCLO6 x x x

3


Course Information

Year ofCurriculum


4 Deep Learning with Python







Prerequisites BMB707


Instructors

Assistants


Deep learning methods, which are a sub-branch of artificial learning, can perform high-level abstract modeling from labeled or unlabeled data. Developments in hardware and algorithms in recent years have enabled these methods to be used frequently in big data analysis, computer visionand natural language processing. This course will study the theoretical and practical aspects behind the popularity of deep learning methods. At the same time, practical experience will be gained.

Course ContentMachine Learning, Deep Learning Tools - Caffe, Torch, TensorFlow, Theano, Optimization, Computer Vision, Big Data, Speech Processing



Learning Outcomes

1. To apply and apply advanced Computer Engineering concepts

2. To work in interdisciplinary interactive research assignments

3. To improve knowledge and yet privatizations in order to adapt to the rapidly changing technologicalenvironment

4. To be able to express his ideas and findings about the research subject effectively in oral and written form.

1

5. Raising awareness to interpret new professional practices and skills.

COURSE CONTENT

Week Topics

1 Introduction Machine Learning

2 Basics Makine Öğrenmesi

3 Deep Learning Tools - Caffe, Torch, TensorFlow, Theano

4 Feedforward Deep Networks

5 Regularization of Deep or Distributed Models

6 Optimization for Training Deep Models

7 Convolutional Networks

8 Midterm Exam

9 Structured Probabilistic Models for Deep Learning

10 Linear Factor Models and Auto-Encoders

11 Computer Vision Applications

12 Big Data Applications

13 Natural Language Processing Applications

14 Speech Processing Applications

15 Final Exam

RECOMMENDED SOURCES

Hands on Machine Learning with Scikit-Learn & Tensorflow by Aurelien Geron, 2019.

ASSESSMENT


Mid-terms 1 20

Quizzes

Homework

Attendance

Seminar

Practice


Project 4 20

2

Field Survey

Workshop

Laboratory

Presentation


Total 6 100



Total 6 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 5 75


Homework 4 10 40

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes


Total Work Load 150




Course Learning

Outcomes


0CLO1 x x x xCLO2 x x x xCLO3 x xCLO4 x x

3

CLO5 x x x

4


Course Information

Year ofCurriculum


4 Data Mining BMB804 Spring 2+1 3 5






Prerequisites


Instructors

Assistants


Data mining is discovery of the knowledge from the huge amount of data. On the other meaning of data mining is the process of prediction about future by the way of computer programs.There are lots of synonyms similar to data mining in the literature. They are “knowledge mining from databases”, “knowledge extraction”, “data/pattern analysis”, “data archaeology”. “Knowledge Discovery From

Databases (KDD)” is the well known one.

Course Content

Data mining concepts, Data preparation techniques, Statistical learning theory, Naive Bayes classification and decision threes, Clustering methods, Associaition

rules



Learning Outcomes

1.Students will gains the ability to learn and apply the basic knowledge of data mining.

2.Students will learn data preprocessing ( data cleaning and entegration) methods.

3.Students will know Data reduction methods.

1

4.Students will learn classification and clustering methods with supervised and unsupervised methods.

5.Student will have knowledge about association rules.

COURSE CONTENT

Week Topics

1 Introduction to Data Mining

2 Data Mining Concepts and Data Preprocessing Techniques

3 Data Reduction and Data Discretization-I

4 Data Reduction and Data Discretization-II

5 Decision Trees and Decision Rules

6 Statistical Classification Methods, Naïve Bayesian Classification

7 Evaluation Methods on classification, Class confusion Matrix

8 Midterm exam

9 Clustering Methods: K-Means Alg. And Hierarchical Clustering

10 Association Rules, Market Basket Analysis, Apriori Algorithm

11Data Warehouse and OLAP Technologies, OLAP Operations in the

Multidimensional Data Models

12 Mining the World Wide Web

13 Classification with Artifical Neural Networks

14 Project presentation

15 Final Exam

RECOMMENDED SOURCES

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

2

Attendance

Seminar

Practice


Project 1 20

Field Survey

Workshop

Laboratory

Presentation


Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 3 45


Homework 5 6 30

Seminar

Presentation

Practice

Laboratory


Project 1 30 30

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 10 10

Quizzes






3

Course Learning

Outcomes


0CLO1 x x xCLO2 x xCLO3 x xCLO4 x xCLO5 x x x

4


Course Information

Year ofCurriculum


4 Genetic Algorithms







Prerequisites


Instructors

Assistants

Objectives of the CourseThe main aim of the course is to learn Genetic Algorithms and Engineering Applications.

Course Content Genetic Algorithms and Engineering Applications



Learning Outcomes

1. To know the basics of the Genetic Algorithm

2. Be able to solve difficult problems without using complex mathematical formulas

3. To know the purpose of use of the Genetic Algorithm

4. To be able to define mutation, fitness, crossover operators

5. To be able to use Genetic Algorithm in optimization problems

COURSE CONTENT

1

Week Topics

1 Introduction to Genetic Algorithm

2 Reasons for Using Genetic Algorithm

3 Difference between Genetic Algorithm and other methods

4 Basic concepts of the Genetic Algorithm (GA)

5 Genetic Operators

6 The Study of the Genetic Algorithm

7 The importance and applications of the Mutation Operator

8 Midterm Exam

9 Conformity and Crossing operators

10 Schema Theorem in GA

11 Simulate Annealing

12 Taboo search

13 Applications of GA in Engineering problems

14 Applications of GA in Engineering problems

15 Final Exam

RECOMMENDED SOURCES

Randy L. Haupt, Sue E. Haupt, "Practical Genetic Algorithms", 2nd edt, 2004.Melanle, M., An Introduction to GeneticAlgorithms, MIT Press,1996.Chambers, L., “Practical Handbook of Genetic Algorithms, CrcPress, 1995.Goldberg, D. E., “Genetic Algorithms in Search, Optimization and Machine Learning”, Addison Wesley, New York, 1989.Gen, M., andCheng, R., “Genetic Algorithms and Engineering Design”, John Wiley&SonsInc., New York, 2000.Kenneth A. DeJong, Evolutionary Computation: A Unified Approach , MITPress, 2006.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation

2


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


4 Introduction to Streaming Data







Prerequisites


Instructors

Assistants


This course will offer to students programming models, algorithms andtools of big data computing to support data-intensive applications. Students will get to knowthe latest research topics of big data platforms.

Course Content

In this course, new computing paradigms that are emerging for big data applications will be covered. These include big data algorithms, big data programming paradigms and platforms, big data analysis tools. In addition, the course will cover a lot of scientific papers.



Learning Outcomes

Students will learn recent research trends and special topics in big data computing area.

Big Data Processing and Analysis concepts will be learned.

Big Data Processing and Analysis skills for developing data-intensive applications will be acquired.

Big Data computing platforms will be analyzed, and the skills to evaluate (performance, scalability,

1

usability criteria) big data computing applications will be gained.

Students may have information about current software used in Big Data Processing.

COURSE CONTENT

Week Topics

1 Introduction to Course

2 Map-Reduce Programming Model

3 Finding Similar Items in Big Data

4 Mining Data Streams

5 Link Analysis in Big Data

6 Frequent Itemsets Mining in Big Data

7 NoSQL Databases

8 Midterm Exam

9 Clustering in Big Data

10 Recommendation Systems for Big Data

11 Dimensionality Reduction

12 Large-Scale Machine Learning

13 Mining Social-Network Graphs

14 Student Presentations

15 Final Exam

RECOMMENDED SOURCES

- Mining of Massive Datasets, Jure Leskovec, Anand Rajaraman, Jeff Ullman,Cambridge University Press, Nov. 2014.

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

2

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






3

Course Learning

Outcomes



4


Course Information

Year ofCurriculum


4 Introduction to Machine Learning







Prerequisites


Instructors

Assistants


This course is intended as an introduction to machine and its use with

examples of

applications within a wide range of domains.

Course Content

1. Introduction to Machine Learning

2. Supervised Learning and Applications

3. Unsupervised Learning and Applications

4. Reinforcement Learning and Applications



Learning Outcomes

1.Student will understand machine learning fundamentals.

2.Student will learn a set of well-known supervised, unsupervised and semi-supervised learning

1

algorithms.

3.Student will able to program solutions to some given real world machine learning problems.

4.Student will complete a project, write report and present in class on a topic in machine learning.

5.Given the parameters of a problem, students should be able to describe the advantages anddisadvantages of different machine learning methods.

COURSE CONTENT

Week Topics

1 Introduction to Machine Learning

2 Supervised Learning

3 Bayes Rule

4 Naive Bayes Theorem

5 Decision Trees

6 Linear Discrimination

7 Artificial Neural Networks

8 MidTerm Exam

9 Support Vector Machines

10 Non Linear SVMs

11 Unsupervised Learning

12 Clustering: K-means, Mixture models

13 Hierarchical Clustering Methods

14 Ensemble Methods: Boosting, Bagging

15 Final Exam

RECOMMENDED SOURCES

- Introduction to Machine Learning, Ethem Alpaydin, The MIT Press,2010- Pattern Recognition and Machine Learning, Christopher M. Bishop, Springer,2006

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


2

Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3

CLO5 x x x

4


Course Information

Year ofCurriculum


4 Genetic Algorithms







Prerequisites


Instructors

Assistants


Course Content



Learning Outcomes

1.With the basic knowledge about e-commerce, predisposition is gained to the implementations in this domain.

2.Concept of e-marketing is defined.

3. Concept of digital marketing and mobil marketing are identified.

4.Integration of social networks and marketing is discussed.

COURSE CONTENT

1

Week Topics

1 Introduction to E-commerce

2 The internet infrastructure: The internet and the World Wide Web

3 Selling on the web: Revenue models and building a web presence

4 Marketing on the web

5 Business to Business Activities: Improving efficiency and reducing costs



8 Midterm Exam


10 Business to Business Activities: Improving efficiency and reducing costs



13 Selling on the web: Revenue models and building a web presence


15 Final Exam

RECOMMENDED SOURCES

- Electronic Commerce - Gary P. Schneider-İnternette Pazarlama - İbrahim KIRCOVA

ASSESSMENT


Mid-terms 1 40

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

2

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev 5 6 30

Seminer

Sunum

Uygulama 1 10 10

Laboratuvar 3 10 30


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav






Course Learning

Outcomes



3


Course Information

Year ofCurriculum


Introduction to Computer Science







Prerequisites None


Instructors

Assistants

Objectives of the CourseTo teach the basics of Computer Engineering and the algorithm concepts to zero-experienced students.

Course Content

History of Computers ; The Basics of Computer Science and Computer Engineering ; Software and Hardware Comcepts ; Computer Architecture ; Data Manipulation ; Signed and Unsigned Integers ; Floating Point Numbers ; Number Systems ; Introduction to Algorithms ; Flowcharts ; Pseudo Code; Input/Outpput ; Arithmetic Operations ; Controls ; Loops ; Introduction to Coding ; Data Types ; Arrays ; Min-MaxProblem ; Strings ; Multi-dimensional Arrays ; Search Algorithms ; Complexity of Algorithms



Learning Outcomes

1. Students will understand fundamental underlying principles concepts of computer engineering.

2. Students will understand how to design correct and efficient algorithms.

3. Students will learn about the process of writing and debugging a program.

1

4. Students will learn how to describe the devised algorithms as flowcharts.

5. Students will be able to know different branches of computer engineering.

COURSE CONTENT

Week Topics

1 History of Computers / Fundamental Concepts of Computer Sciences and Engineering

2 Software and Hardware Concepts

3Computer Architecture / Data Manipulation / Number Bases, Conversion / Signed and Unsigned Numbers / Floating Point Numbers

4 Algorithm Concept / Flow Charts / Pseudo Code

5 Input/Output / Arithmetic Operations / Control Flows

6 Loops

7 Introduction to Coding

8 Basic Data Types

9 Midterm 1

10 Strings

11 Multi-dimensional Arrays

12 Search Algorithms

13 Sort Algorithms

14 Complexity of Algorithms

15 Final

RECOMMENDED SOURCES

Brookshear J.G., “Computer Science: An Overview”, Pearson International Edition, 2007

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework 3 10

Attendance

Practice

Seminar

Practice

2


Project

Field Survey

Workshop

Laboratory

Presentation


Total

Contribution of Semester Studies to the Success Grade 40

Contribution of the Final Exam to the Success Grade 60

Total 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 3 45


Homework 3 8 24

Seminar

Presentation

Practice

Laboratory


Project

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 8 8

Quizzes 1 16 16


Final examination

Total Work Load 120




Course Learning

Outcomes


0

3

CLO1 x x xCLO2 x x xCLO3 x x x x xCLO4 x x x xCLO5 x x x

4


Course Information

Year ofCurriculum


3Software Engineering BM601 Spring 2+2 4 5






Prerequisites None


Instructors

Assistants


The objective of this course is to provide students a commonunderstanding of software engineering principles. It is organized so as to,first, provide a general introduction to software development and identifythe important phases of any software project. Then, each of the phases isexamined in detail, in order to give the student a picture of the currentstate of software development.

Course Content

In this course, students learn the theoretical and practical aspects ofspecification and design, development, verification and validation andtesting stages of SE. More, this course enables students to realizesoftware specification and design phases of sample projects with realclients.


Lecture


Learning Outcomes

1. Define engineering, software, computer and system engineering

2. Define software processes

3. Gather the software requirements

1

4. Define software design and architecture

5. Learn the software verification and validation

COURSE CONTENT

Week Topics

1 Introduction to Software Engineering

2 Software Processes

3 Agile Software Development

4 Requirements Engineering

5 Project Meeting and GUI Programming

6 System Modeling

7 Architectural Design

8 Midterm Exam

9 Project Meeting and Collaborative Development

10 Design and Implementation

11 Project Management

12 Software Testing

13 Project Meeting and Test-Driven Development

14 Software Evolution

15 Final Exam

RECOMMENDED SOURCES

Software Engineering 10, Ian Sommerville, 10th Ed. Addison Wesley, 2015, 978-0133943030

ASSESSMENT


Mid-terms 1 30

Quizzes

Homework

Attendance

Practice

Seminar

Practice


Project 1 30

Field Survey

2

Workshop

Laboratory

Presentation 1 40

Final examination

Total 3 100



Total 3 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)


15 4 60


Homework

Seminar

Presentation

Practice

Laboratory


Project 11 5 55

Field Survey

Workshop

Others (………………………………………………………………)

Mid-terms 1 15 15

Quizzes


Total Work Load 150




Course Learning

Outcomes


0CLO1 x x xCLO2 x x x x xCLO3 x x xCLO4 x x x xCLO5 x x

3


Course Information

Year ofCurriculum


1 Turkish Language I

BMB102 Güz 2+0 2 2






Prerequisites


Instructors

Assistants


Structure of Turkish and acquisition of basic grammar rules, comprehension ofreading texts, expanding learners’ vocabulary knowledge.

Course ContentHistory and basic rules of Turkish language, reading exemplary literary and scientific texts.



Learning Outcomes

Know about the languages used in the world and the place of Turkish among world languages.

Acquires the correct use of spelling rules and punctuation marks

Acquires a larger vocabulary

Can use science and knowledge in a better way.

Acquires reading habit and pleasure

1

COURSE CONTENT

Week Topics

1Introduction of the content of the the course and references ofcourse.

2 Communication.

3

Definition of language, characteristics of languages, the relationship between language and culture, relationship between language andnationality. Formal and informal language.

4Languages of the world . Historical development of Turkish and theplace of Turkish among the languages of the world.

5Current problems of the Turkish in light of the modern texts. The problems with the spelling of the words in Turkish accompanied by compiled texts.

6Spelling rules. Punctuation. The importance of the punctuation.Application of punctuation.

7 Spelling rules accompanied by contemporary texts.

8 Mid-term exam.

9 Text analysis: Article

10 Written expression: writing an essay

11 Writing exercises,text analysis.

12 Formal writing styles.

13 Expression disorders. Exercises.

14Analysis of expression disorders accompanied by contemporarytexts.

15 Final Exam

RECOMMENDED SOURCES

Class notesYusuf Çotuksöken, Üniversite Öğrencileri İçin Uygulamalı Türk Dili 1. ve 2. Cilt, Papatya Yayıncılık, İstanbul 2001.Doğan Aksan, Türkiye Türkçesinin Dünü, Bugünü, Yarını, Bilgi Yayınları,İstanbul 2000.T. Nejat Gencan, Dilbilgisi, Ayraç Yayınları, Ankara.Doğan Aksan, Türkçenin Sözvarlığı, Engin Yayınları, Ankara.Doğan Aksan, Türkçenin Gücü, Bilgi Yayınevi, 4. Basım, Ankara 1997.Ömer A. Aksoy, Dil Yanlışları, Adam Yayıncılık, İstanbul 1999.Feyza Hepçilingirler, Türkçe “Off”, Remzi Yayınları.Talat Tekin-Mehmet Ölmez, Türk Dilleri/ Giriş, Simurg Yayınları, İstanbul 1999.Yazım Kılavuzu, Türk Dil Kurumu, 2012, Ankara.Necmiye Alpay, Türkçe Sorunları Kılavuzu, Metis Yayınları, İstanbul 2000.

ASSESSMENT


Mid-terms 1 40

2

Quizzes

Homework

Attendance

Seminar

Practice


Project

Field Survey

Workshop

Laboratory

Presentation


Total 2 100



Total 2 100

ECTS/WORKLOAD TABLE


TotalWorkload

(Hour)



Ödev

Seminer

Sunum

Uygulama

Laboratuvar


Proje

Arazi Çalışması


Diğer (………………………………………………………….)

Ara Sınav 1 10 10

Kısa Sınav





3


Course Learning

Outcomes



4

BOLOGNA COURSE INFORMATION FORM

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