Practical Decision Making Using Data Science
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ASIA’S #1 UNIVERSITY #11 GLOBALLY Source: QS World University Rankings 2021 Practical Decision Making Using Data Science 6-MONTH PROGRAMME | ONLINE | MASTERCLASSES No programming experience required
Transcript of Practical Decision Making Using Data Science
ASIA’S#1
UNIVERSITY#11
GLOBALLYSource: QS World University Rankings 2021
Practical Decision Making Using Data Science6-MONTH PROGRAMME | ONLINE | MASTERCLASSES
No programming experience required
Companies the world over are largely relying on data-driven decision making across functions.
From strategic calls on new business initiatives to decisions on optimising marketing and
pricing, driving efficiencies, automation and enhancing customer service and experience, every
aspect of business is being powered by data-driven insights.
There is hardly any business function that is untouched by data today. From Business Heads to
Delivery Managers and CXOs there is a need to update, upskill or re-skill. They would need to
complement their domain expertise with an understanding of the basic statistics that underpin
Data Science, working knowledge of application tools and implementation capabilities.
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WHY MANAGERS NEED TO E XCEL ATDATA- DR IVEN DECIS ION MAKING
The goal is to turn data into information and information into insight.- Carly Fiorina, Former Chief Executive Officer, Hewlett Packard
Recruitment patterns are echoing this trend.
According to LinkedIn, jobs in Data Science have
grown by 650% since 2012, with an estimated
11.5 million new positions being created by 2026.
This large scale adoption of Data Science is
driving the demand for:
Business Managers with strong domain
expertise who understand the techniques and
principles needed to ask the right questions
and extract insights from data
Managers who can work with and lead teams of
Data Science practitioners
DATA SCIENCE
Coding Statistics
Domain
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ABOUTTHE PROGR AMME
WHAT YOU WILL LEARN AND HOWIn this programme you will learn how data-centric organisations leverage the data at their
disposal, make decisions, and use Data Science to boost their businesses. Whether you are a
functional manager, an analyst, a business leader or an entrepreneur, you are going to make
better and more informed decisions using the tools you will learn in this programme.
This programme does not get mired in the minutiae or the technical details of Data Science.
Instead, it helps you deal with practical situations with the right approach. You will learn to ask
the right questions, structure the problems better, perform suitable analytics, and develop
good judgment when it comes to interpreting results and identifying biases.
You will learn by hands-on - through a series of well-structured projects where you apply the
concepts you have learned, and in the process, also build your skills in the tools of the trade -
Excel and cloud-based platforms that support data analysis. The programme does not assume
you are comfortable writing code, and builds your skills in this area from scratch. The goal is to
help you make good business decisions using Data Science, no matter which industry you
represent or what function you work in.
WHO IS TH ISPROGR AMME FOR?
Product/Project/Programme Managers
New Team Leads and Executives
Sales/Marketing/Delivery/Account Managers
CXO/Directors
Experienced Entrepreneurs who wish to expand
their skill set
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This programme is best suited for mid to senior
managers who have a strong understanding of their
respective domains and wish to learn analytics to aid
their decision making skills. These would include:
LEARNING OUTCOMES
Develop the capability to understand how to use data to get meaningful results for your
business
Acquire working knowledge of frameworks & toolkits to quickly evaluate Data Science
problems
Learn how to use Excel and KNIME for building Data Science applications
Understand the business landscape and types of business problems that can be solved
using Data Science
Equip yourself with sufficient analytics knowledge to guide your team in the right direction
Through this programme, you will:
Note - No programming experience required
PROGR AMME STRUC TURE &HIGHL IGHTS
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Certificate of Completion from NUS Business School
6 Projects including a Capstone Project to prepare you for real-world problems
Industry-relevant learning material from NUS faculty and industry experts
4 to 6 Hours of learning commitment per week
Monthly projects with guidance and learning support
6-Monthprogramme
CURR ICULUM
The curriculum covers an in-depth and comprehensive journey in Data Science from the lens of
a Business Manager. Participants harness the skills required to analyse data and extract
information to make sound business decisions and strategies.
Month 1: Foundations of Data-Driven Decision Making
Identify, prepare and analyse data to derive maximum value
Visualise data intelligently to deliver the right message
Driving success in Data Analytics projects
Arm yourself with the core tools to deal with any problem using a data-driven
approach – from structuring the problem to data analysis to visualisation.
Topics include:
Bayes Theorem and Bayesian Decision Making
Simulations to make decisions under uncertainty
Decision trees and their uses in a variety of situations
Real-world problems come with limited data and a lot of uncertainty. Learn
how to deal with these kinds of problems using the data available.
Topics include:
Real-world problems come with limited data and a lot of uncertainty. Learn
how to deal with these kinds of problems using the data available.
Topics include:
Linear Optimisation
Sensitivity Analysis and Shadow Price
Use optimisation to make informed decisions, and learn tools to validate and
understand the sensitivity of your analyses.
Topics include:
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Month 2: Decision Making Under Uncertainty
Month 3: Optimal Decision Making
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Month 5: Experiments and Causal Inference
Randomized Controlled Trials
Instrumental variables
Difference in differences
Design practical experiments to gain insights, and learn to deal with external
factors and events outside your control.
Topics include:
Month 6: Data Science to Drive Business Value
Driving digital transformation within the organisation
Aligning organisations and teams for data-driven approaches
Making the business case for Data Science
Learn how to put the tools and techniques you have learned to the service of
business growth and value generation.
Topics include:
Month 4: Predictive Analytics
Linear & Logistic RegressionClassification & Regression Trees
Clustering
Learn supervised learning to make predictions using data, and unsupervised
learning to learn patterns from data.
Topics include:
Cross-Validation
CER T IF IC ATE
APPL IC AT ION PROCESS
PROGR AMME DUR AT ION AND FEE DETAIL S
Fees: USD 2200Programme Duration: 6 Months
Upon successful completion of the programme, learners will receive a digital certificate from NUS.
Step 1Fill the Application FormApply by filling a simple
online application form.
Step 2Interview ProcessGo through a screening
call with the Admission
Director’s office.
Step 3Join ProgrammeAn offer letter will be rolled
out to a select few
candidates. Secure your seat
by paying the admission fee.
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Professor Keppo teaches risk management and analytics programmes, and directs analytics
executive education programmes at NUS Business School. He is also Research Director of the
Institute of Operations Research and Analytics at NUS. Previously, he taught at the University
of Michigan.
He has several publications in the top-tier journals such as Journal of Economic Theory, Review
of Economic Studies, Management Science, Operations Research, and Journal of Business on
topics such as investment analysis, banking regulation, learning, and strategic incentives. His
research has been featured in numerous business and popular publications, including the Wall
Street Journal and Fortune. Professor Keppo’s research has been supported by several Asian,
European, and US agencies such as the National Science Foundation. He serves on the
editorial boards of Management Science, Mathematics of Operations Research, and Journal of
Risk. He has consulted several startups, Fortune 100 companies, and financial institutions.
FACULT Y
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PROFESSOR JUSSI KEPPOAssociate Professor and Dean's ChairResearch Director, Institute of Operations Research and AnalyticsDepartment of Analytics & Operations, NUS Business SchoolNational University of Singapore
Dr. Tan Hong Ming is a lecturer at the Department of Analytics and Operations, and a
research fellow in the Institute of Operations Research and Analytics, IORA, at the National
University of Singapore (NUS). His research includes decision making under uncertainty,
information economics, sports analytics, and causal inference. Currently, he is leading three
industry research projects. The first is on field studies of pilot training, and the second is on
demand modeling and price optimisation, both for a major airline carrier. The third one is on
forecasting possible quality issues and optimal responses to the forecasts for a leading global
medical device company. He teaches analytics for undergraduate and graduate courses, as
well as in analytics executive education programmes at NUS. He has won several teaching
awards. He was a lecturer at Temasek Polytechnic and has co-authored three textbooks.
DR. TAN HONG MINGLecturer and Research FellowDepartment of Analytics and Operations, NUS Business School, Institute of Operations Research and Analytics National University of Singapore
ABOUT NUS
NUS IS RANKED
QS WORLDUNIVERSITYRANKINGS
ASIA’S
#1 QS WORLDUNIVERSITYRANKINGS#11
NUS Business School is internationally renowned for its academic rigour,
enterprising research and teaching excellence
LEADING BUSINESS SCHOOL IN ASIA
NUS has earned a reputation for combining the strengths
of Western schools of thought and practices with unique
Asian perspectives
BEST OF EAST AND WEST
NUS is ranked 14th in the world by Financial
Times (FT) Global MBA Rankings 2021
WORLD RANKING
14th
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