Introduction - ETH Zürich · PDF fileDetailed illustration in a next lecture. Tip ......

IntroductionEvangelos Pournaras Izabela Moise Dirk Helbing

Evangelos Pournaras Izabela Moise Dirk Helbing 1

Outline

1 Data Science

2 Course Description


Part 1 - Data Science


What is Data Science

A collection of orchestrated methods from different scientific fieldseg statistics computer science etc that provide understanding ofdomain data and result in data-based products and services


Is Data Science about Big Data I


Is Data Science about Big Data II

Itrsquos more about using the right dataand asking the right questions


What about Techno-socio-economic Systems


ICT amp Techno-socio-economic Systems

bull Embedded ICT systems in most societal domains How

bull Internet of Things pervasiveubiquitous computing advancednetworking systems inter-operability Result

bull A new explosion of data sources Opportunities

bull Understanding improving managing amp sustaining our complexsociety Threats

bull Privacy discrimination misinterpretations over-fitting etc


Threats I


Threats II


Who is a Data Scientist

bull A statistician

bull A computer programmer

bull Both and More

TipDomain knowledge can be more valuable than machine learning datamining etc


Real-world Profile I


Real-world Profile II


More about Data Scientists


Part 2 - Course Description


Course ObjectivesQualify you with knowledge amp skills to tackle real-world problemsusing data

1 Acquiring domain knowledge and understanding2 Better understanding and interpretation of data

3 Awareness about the applicability of different data sciencemethods

4 Development of technical skills eg programming use ofdifferent tools etc

5 Presenting scientific results both written and orally


Course Prerequisites

Some programming skills are required eg skills for the material ofthis course

1 JavaC++

2 UNIX

Didnrsquot you have an opportunity to practice this earlier

No problem this is a golden opportunity

TipProgramming skills will make you more flexible and efficient datascientist


Assessment

bull Seminar thesis

bull 100 of the grade no exams

bull Detailed illustration in a next lecture

TipStart early Give the opportunity for your project and your skills todevelop during the course


Lectures

bull Every Tuesday 1000-1200 at LFW B 1

bull Participation is not obligatory but highly recommended

bull 60 minutes lectures followed by 40 minutes interactivediscussions

bull Opportunity to discuss your project

bull Lectures at httpwwwcossethzcheducationdatasciencehtml


Subjects I

1 Applications - 2 weeksndash Smart Grids geolocation traffic systems Planetary Nervous

System etcndash Tools NervousNet

2 Data Science Fundamentals - 2 weeksndash databases data types data collection data pre-processing

plotting visualization etcndash Tools Java AWK R MySQL Gnuplot Gephi etc

3 Data Mining and Machine Learning - 3 weeksndash classification clustering prediction neural networks etcndash Tools Weka

4 Big Data Analytics - 2 weeks


Subjects II

ndash MapReduce parallel computing etcndash Tools Hadoop Spark Mahout etc

5 Real-time Data Analytics - 1 weekndash data streaming social media etcndash Tools Spark Streaming Storm

6 Other - 4 weeksndash Project workndash Tools LATEX Github etc


Lectures OutlineLecture 01 (170215)IntroductionLecture 02 (240215)Seminar ThesisLecture 03 (030315)ApplicationsLecture 04 (100315)ApplicationsLecture 05 (170315)Data Science FundamentalsLecture 06 (240315)Data Science FundamentalsLecture 07 (310315)Data Mining and Machine Learning

Lecture 08 (140415)Data Mining and Machine LearningLecture 09 (210415)Data Mining and Machine LearningLecture 10 (280415)Big Data AnalyticsLecture 11 (050515)Big Data AnalyticsLecture 12 (120515)Real-time Data AnalyticsLecture 13 (190515)Oral PresentationsLecture 14 (260515)Oral Presentations


How to contact us

Communication

bull Discussion session in the course

bull E-mail with subject[DATA-SCIENCE-COURSE-2015]ltotherinfogtto

ndash Evangelos Pournaras epournarasethzch andorndash Iza Moise imoiseethzch

Supervision - strictly for issues not addressed in the course

bull Wednesdays 1400-1600


Proposed Literature

B Ellis

Real-Time Analytics Techniques to Analyze and Visualize Streaming Data

Wiley Publishing 1st edition 2014

J Han

Data Mining Concepts and Techniques

Morgan Kaufmann Publishers Inc San Francisco CA USA 2005

T White

Hadoop The Definitive Guide

OrsquoReilly Media Inc 2012

I H Witten E Frank and M A Hall

Data Mining Practical Machine Learning Tools and Techniques

Morgan Kaufmann Publishers Inc San Francisco CA USA 3rd edition2011


What is next

bull Seminar thesis - attendance is strongly recommended

bull Examples and applications


Outline

1 Data Science

2 Course Description





















Threats I


Threats II



bull A statistician


bull Both and More



















1 JavaC++

2 UNIX





Assessment

bull Seminar thesis





Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next























Threats I


Threats II



bull A statistician


bull Both and More



















1 JavaC++

2 UNIX





Assessment

bull Seminar thesis





Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




Threats II



bull A statistician


bull Both and More



















1 JavaC++

2 UNIX





Assessment

bull Seminar thesis





Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next





bull A statistician


bull Both and More



















1 JavaC++

2 UNIX





Assessment

bull Seminar thesis





Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




















1 JavaC++

2 UNIX





Assessment

bull Seminar thesis





Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




Assessment

bull Seminar thesis





Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




Lectures







Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




Subjects I








Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




Subjects II








How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next







How to contact us

Communication







Proposed Literature

B Ellis



J Han



T White







What is next




Proposed Literature

B Ellis



J Han



T White







What is next




What is next




Introduction - ETH Zürich · PDF fileDetailed illustration in a next lecture. Tip ......

Documents

Transcript of Introduction - ETH Zürich · PDF fileDetailed illustration in a next lecture. Tip ......