Data Science & Analytics for Strategic Decisions Programme

Harness the power of data science to uncover actionable insights and transform your organisation’s decision-making

Download Brochure

Get Your Brochure

Course Dates

STARTS ON

27 June 2024

Course Duration

DURATION

14 Weeks, Online
4-6 hours per week

Course Fee

PROGRAMME FEE

US$2,000 and get US$200 off with a referral

Course Information Flexible payment available
Course Information Special group enrolment pricing

Applications close on 26 June 2024

Apply before 26 June 2024 and avail early bird tuition assistance of USD50. Use code APAC50ALL9153 while applying.

New features:
●   Live session with faculty
●   Live sessions with Industry Experts
●   Tools to be taught - XLSTAT, Excel and Tableau
●   Capstone Project

What You Will Learn in the Programme?

  • Create and implement business strategies leveraging data science.
  • Make data-driven decisions to solve business problems using data insights.
  • Demonstrate how analytics can be combined with experiments to make data-informed recommendations for business growth.
  • Explain the key challenges and risks in data science projects.
  • Evaluate an organisation’s data strategy and recommend ways to achieve a sustainable competitive advantage.
  • Analyse organisational needs and drive business improvement through data science future trends.

Programme Highlights

90+ Video Lectures

100+ Pre-Recorded Video Lectures* from SMU faculty with for self-paced learning interspersed with live lectures from renowned SMU faculty and industry practitioners

30 Assignments

30 **Assignments

10+ Industry Examples

10+ Industry Examples

6 Discussion Boards

6 Discussion Boards

6 Case Studies

9+ Case Studies

3 Live Sessions with Faculty

3 Live Sessions with Faculty

Note: -The programme highlights presented above are approximate, and subject to change depending on the availability and expertise of the teaching faculty, as well as the programme's desired outcomes.
-The programme is designed to be delivered approximately over 9 to 10 months in a calendar year, including some occasional breaks that may be provided. This is only indicative. The actual calendar time may be more or less by a few weeks depending on the number of topics covered and other variables like breaks provided/not provided."
-**Assignments are reviewed either by success coach who is available to support participants in their learning journey and/or by the Emeritus grading team. The final number of quizzes, assignments and discussions will be confirmed closer to the programme start.
-*This is a majorly self-paced online programme with some live sessions with programme faculty. Post- session video recordings will be available for up to 12 months after programme completion. We have a curated panel of industry practitioners who will be conducting the weekly live doubt-clearing sessions.

Live sessions on XLSTAT

The live sessions will cover- Installation guide and how to get some basic descriptive statistics?
Followed by some demonstration and practice assignments.

Tools Covered

Tools

Note: The tools will be taught by teaching faculty, industry practitioners, or linked to relevant knowledge bases for your reference and self-guided learning

Programme Modules

    • Key terminologies of data science
    • Different levels of data analytics and their significance to decision-making
    • Data features and insights to attain sustainable competitive advantage
    • Applications of data analytics and its role in creating new business opportunities
    • Analytical approach to resolve a business problem
    • Is your organisation is data-driven
    • Trends in data and obtaining related insights to enhance business performance
    • Impact an organisation’s omnichannel strategies have on sales
    • How to identify appropriate data/insights
    • Comparison of independent data sets to obtain insights
    • How to apply strategic decision-making using said techniques
    • Regression to analyse the strength/impact of variables
    • Predict variable impact using optimal model fit and regression effects
    • Logistic regression model to test and predict expected outcomes
    • Apply predictive analytics to organisational events to advance strengths and counter threats
    • Correlation and causality and their significance to enhancing business performance
    • Experimentation for business problems to make effective inferences
    • Multivariate, A/B and Multi-Armed Bandit testing
    • Effectiveness of using experimental design to make data-informed recommendations for business growth
    • Recommendation Systems

      • Recommendations and Ranking
      • Collaborative Filtering
      • Personalized Recommendations
    • ML and its role in driving organisational productivity
    • Apply ML algorithms to achieve optimal analytical accuracy
    • Programme-building facets of neural networks and deep learning
    • Combine analytics with experiments to produce effective business strategies
    • Decision Making Under Uncertainty

      • Bayesian Decision Making
      • Simulations to make decisions under uncertainty
    • Optimal Decision Making

      • Linear Optimisation
      • Sensitivity Analysis and Shadow Price
    • Driving digital transformation within the organisation
    • Change management: The role of data analytics, machine learning and its applications
    • Aligning organisations and teams for data-driven approaches
    • Making the business case for Data Science
    • Data Storytelling with Visualisation using Tableau
    • Disruptive innovation
    • Distilling value from analytics
    • Developing a strategy roadmap, privacy implications, traps and myths
    • Customer-centric analytics in retail and media
    • Business process analytics
    • Domain exposure
    • Key challenges to data science projects and their solutions
    • Delta Framework and Delta Plus Model
    • Project-level risks and examples of failed data science projects
    • Predict the success of big data project using DATA technique
    • Drivers, expected outcomes, and technology enablers for Industry 4.0
    • Components for AI success
    • Challenges in the implementation of AI in systems
    • Evaluate an organisation’s digital transformation journey and sustain a competitive advantage
    • Overview of ChatGPT and OpenAI
    • Timeline of NLP and Generative AI
    • Frameworks for understanding ChatGPT and Generative AI
    • Implications for work, business, and education
    • Business roles to leverage ChatGPT
    • Futureproofing organisations to incorporate Generative AI into workflow
    • Prompt engineering for fine-tuning outputs
    • Safeguards and risk mitigation measures

Capstone Project

The Capstone Project will give the participants an opportunity to apply the learnings from this course to a key industry or a real-world situation.

Industry Examples

Through real-world examples from multiple industries, you'll see how the theories are put into practice.

Facebook

Facebook

Understand how proprietary data was collected by Facebook for targeted advertising.

Tesla

Tesla

Learn about how Tesla uses Recurrent Neural Networks(RNN) in autopilot cars.

Google

Google

Understand how AI runs Google Adwords to decide advertisement ranking.

Tinder

Tinder

Learn how Tinder uses the data-enabled network effect for New Smart Photo algorithm.

Walmart

Walmart

Identify how Walmart uses historical data for data-driven predictive technology to predict shopping pattern during natural calamities.

Pandora

Pandora

Understand how Pandora uses data insights to improve their service/product offerings.

Other companies that are included as examples or as use cases in the programme include Apple, Netflix, Google Trends, Spotify, Microsoft etc.

Note: All brand, product and company names are trademarks™ or registered® trademarks of their respective holders. Use of them does not imply any affiliation with, endorsement by, or association of any kind between them and programme owners.

Why Enrol in Data Science & Analytics for Strategic Decisions?

Enterprises across the globe are shifting their focus to data-driven goals and decision-making. In fact, the International Data Corporation reports that worldwide data will grow 61% to 175 zettabytes by 2025*. So, why is data science so important? Because it enables organisations to efficiently process and interpret data that can be used to make informed business decisions & drive growth, optimisation and performance.

In the online Data Science & Analytics for Strategic Decisions programme—offered by Singapore Management University—you can learn how to process and understand data that can be used to drive better, smarter decisions within your organisation.

*Source: IDC, 2021

22%

is the expected rise in employment of data scientists by 2030 - much faster than the average for all occupations.

SOURCE: US Bureau of Labor Statistics, 2021

95%

of businesses cite the need to manage unstructured data as a problem for their business.

SOURCE: SharesPost, 2019

*The schedule of live sessions and profile of Industry experts is subject to change and confirmation will be provided post programme start.

Case Studies

The Weather Company: Creating Consumer Apps that Leverage Big Data

The Weather Company: Creating Consumer Apps that Leverage Big Data

Iuiga’s Challenge: Is Omni-Channel Worth It?

Iuiga’s Challenge: Is Omni-Channel Worth It?

3M Moves to Customer Focus Using a Global Data Warehouse

3M Moves to Customer Focus Using a Global Data Warehouse

Advertising Experiments at RestaurantGrades

Advertising Experiments at RestaurantGrades

Predicting Customer Churn at QWE Inc

Predicting Customer Churn at QWE Inc

Digital Transformation of the Certis Group

Digital Transformation of the Certis Group

Data Analytics at DBS Group Audit: The Future of Auditing is Auditing the Future

Stitch Fix: Revolutionizing Personalization with Data

Disney+ and Machine Learning in the Streaming Age

Programme Faculty

Faculty Member Sandeep R. Chandukala, PhD

Sandeep R. Chandukala, PhD

Associate Professor of Marketing

Sandeep serves as Associate Professor of Marketing. Prior to joining SMU, Sandeep worked at 3M and before that he worked as a Jr Faculty Fellow at the Indiana University’s Kelley School of Business. He has a PhD in Marketing (with a minor in Statistics) from The Ohio State University... More info
Faculty Member Michelle Cheong, PhD

Michelle Cheong, PhD

Professor of Information Systems (Education); Associate Dean, SCIS Post-Graduate Professional Education; Director, Doctor of Engineering

Professor Cheong has served a variety of academic appointments at SMU since 2005, including as a Lecturer, Assistant Professor and Associate Professor of Information Systems... More info
Faculty Member Hady W. LAUW

Hady W. LAUW

Full-time Faculty, Associate Professor of Computer Science; Director, BSc (Computer Science) Programme; Lee Kong Chian Fellow

Hady W. LAUW serves as Associate Professor of Computer Science at the School of Computing and Information System of Singapore Management University (SMU)... More info
Faculty Member SUN SUN LIM

SUN SUN LIM

FULL-TIME FACULTY, COLLEGE OF INTEGRATIVE STUDIES, Professor of Communication & Technology, Vice President, Partnerships and Engagement

Sun Sun Lim serves as Vice President, Partnerships and Engagement at the Singapore Management University where she’s concurrently working as Professor of Communication... More info

Who Is This Programme For?

The programme is designed for both tech and non-tech professionals —No coding is required; however, a basic knowledge of Excel would be beneficial. Industries and Functions that can benefit include:

Industries:
IT, E-Commerce, Computer Software, Finance, Marketing and Advertising, Banking, Education Management, and Management Consulting

Functions:
Engineering, Programming, Technology, General Management, Marketing, Finance, Operations, and HR Functions

This programme is especially helpful for professionals who aspire to:

  • Transition into a data-centric senior management role
  • Gather analytical expertise to handle greater responsibilities
  • Utilise predictive models to build effective strategies that address key issues in business operations and product quality
  • Become a leader for sustainable business growth
  • Spearhead complete ownership of key business tasks and understand underlying strategic implications

Testimonials

I like the case studies in the modules, which allow me to be more creative in finding ideas for business development for my company.

— Sim Kay Huei, Manager

Based on my limited understanding:

The program should have covered the most, or if not, lots of data science related topics for various purposes, e.g. business decision making, research, reporting etc.

The program should also be suitable for both beginner and intermediate learners on data science.

For beginners or busy-person (like me), though the course content cover lots of data science topics, the required assignments are generally focusing a few relatively simple concepts and skills. Thus it is not complicated to complete them. But for newbie learner like me, if I want to learn and go deeper to understand every topics within limited time, it is quite challenging. Nonetheless, the course provide me a useful guideline and window to extend further learning on data science.

For intermediate learners, as they have the baseline knowledge and skills on statistics or relevant data science knowledge or practice, the course should be able to further expand their knowledge and relevant skills. Not only could they complete all the self-study assignments, but also they have the opportunities to consider explore more challenging analysing tasks, and the program lead Kelvin is always willing to help. There is one advanced learner in this batch, he completed all the analysis tasks using Python, which is considered quite high level to most beginners like me.

— Peter Guan Ming, Principal Physiotherapist

This was a useful course for me as a board director as I was better able to understand data science and how it can be leveraged for competitive business advantage. It has enabled me to provide better governance over data and innovation.

— Tunku Alina Alias, Independent Director

Past participants of Emeritus work at

Note: *All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

Upon successful completion of the programme, participants will be awarded a verified digital certificate by Singapore Management University.

Download Brochure

All certificate images are for illustrative purposes only and may be subject to change at the discretion of Singapore Management University.

Past Participant Profiles

The Learning Experience

What is it like to learn with the learning collaborator, Emeritus?

More than 300,000 professionals globally, across 200 countries, have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programs said that their learning outcomes were met or exceeded. All the contents of the course would be made available to students at the commencement of the course. However, to ensure the program delivers the desired learning outcomes, the students may appoint Emeritus to manage the delivery of the program in a cohort-based manner during the course period the cost of which is already included in the overall Course fee of the course.

A dedicated program support team is available 7 days a week to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.

Emeritus Career Services

Stepping into a business leadership career requires a variety of job-ready skills. Below given services are provided by Emeritus, our learning collaborator for this program. The primary goal is to give you the skills needed to succeed in your career; however, job placement is not guaranteed.

Emeritus provides the following career preparation services:

●   Resume building videos

●   Interview preparation videos

●   Linkedln profile building videos

●   Interview guidebooks

●   Glossary of resume templates

Please note:

SMU or Emeritus do not promise or guarantee a job or progression in your current job. Career Services is only offered as a service that empowers you to manage your career proactively. The Career Services mentioned here are offered by Emeritus. SMU is not involved in any way and makes no commitments regarding the Career Services mentioned here

Early applications encouraged. Limited seats are available

Apply Now

Early registrations are encouraged. Seats fill up quickly!

Flexible payment options available. Learn more.