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Short Course

Data Strategy

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised3Classroom LearningTGS-2022012359

Course Overview

With the increased production of data and the storage and availability of digital data, organisations have become more of a data business. By “data business”, organizations can make use of the data it has stored to make better decisions and improve its operations, or it can turn data into its additional business by monetizing the data it has. Big Data Analytics is no longer a “good to have” feature in any organisation’s suite of functions, it has become a “must have” activity. The key question has become “How could organizations turn Big Data Analytics into common practices?”. Focused on the understanding of Big Data Analytics, this course explores how organizations could use their well-captured data to strategize and reshape their organisations for greater benefits, productivity, and effectiveness.

Course Objectives

This course will enable participants to:

  • Understand what big data is and how Big Data Analytics can help organizations achieve a competitive advantage.
  • Appreciate the benefits and insights that Big Data Analytics bring to the organisations.
  • Learn how to make strategic use of the data available in organisations.
  • Learn how to use data to improve business decisions and operations.
  • Learn how to monetise data to increase the organisation’s revenue.

Job Role Readiness

Data Analysts

Prerequisites

Diploma (or equivalent).

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This programme is part of

  • Professional Certificate in Data Strategy and Storytelling

    • Types of Available Fundings

  • SkillsFuture Funding
  • SkillsFuture Credit
  • Enhanced Training Support
  • SFEC
  • UTAP
  • PSEA

    • Testimonials


    Dr Yeo Wee Kiang has exceptional teaching techniques unique with industry related examples.

    Dr Yeo is an engaging lecturer who has interesting anecdotes from his experience and shares it generously during the course. Most of the insights are very applicable and invaluable.

    Dr Yeo Wee Kiang was approachable and engaging. He also provided relevant case examples throughout the course for our ease of understanding. It has been an enjoyable learning experience under him.

    Appreciate the good mix between theory, practical examples and learning of skills.

    Useful course. Highly recommended!

    The lecturer [Dr Yeo Wee Kiang] is very engaging.

    Highly relevant course that is/will be relevant for the future.

    Instructors


    Dr Yeo Wee Kiang

    Dr Yeo Wee Kiang

    Dr Yeo Wee Kiang is a Senior Lecturer at the Department of Information Systems and Analytics in the NUS School of Computing, where he is dedicated to researching the use of technologies like Adaptive Learning and Large Language Models (LLMs) to create personalized and engaging computing education experiences. With a PhD from NUS focused on machine learning and data mining for pharmaceutical drug discovery, Dr Yeo brings practical industry experience as the former Director of Data Science at a food tech startup, where he led a team applying AI and machine learning to enhance nutritional value. His diverse background includes being an Adjunct Lecturer in the Department of Economics at NUS Faculty of Arts and Social Sciences, helming the Big Data Analytics module in the Master of Economics programme from 2019 to 2023, and teaching Python programming and data analytics at Nanyang Business School. Prior to his academic appointments, Dr Yeo was the Lead Instructor for Data Science at a New York-based commercial Continuing Education and Training (CET) provider, teaching aspiring adult learners in Hong Kong, Sydney, and Singapore. He also holds the WSQ Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning Singapore. As part of the NUS ACE (Advanced Computing for Executives) teaching team, Dr Yeo specializes in technical training and practical computing education focused on data analytics, machine learning, and Python, aiming to equip professionals with in-demand Data Science skills.

    Ms Samantha Sow

    Ms Samantha Sow

    Ms. Samantha Sow is currently a Senior Lecturer in the department of Information Systems and Analytics at the National University of Singapore (NUS). She has over 8+ years of experience in Business Analytics and Data Science and she conducts training for both government agencies and corporate clients. Before joining NUS, she lectures at Temasek Polytechnic, teaching Business Analytics and Data Science to professionals, managers and executives (PMEs). Prior to being an academia, Samantha worked in the research and development at Infineon Technologies. Her research and project areas include Business Analytics, Data Mining, Predictive and Prescriptive Analytics. She has a passion for engaging and inspiring participants to enhance their workplace analytics capabilities and increase business intelligence quotient within their organisations. Her interests lie in the applications of data analytics, predictive modelling and optimization techniques to derive actionable insights for commercial effectiveness. She is familiar with typical analytics tools such as Python, R, and SAS, SPSS and Tableau. She also has working knowledge in the area of Analytics, Data Science and Machine Learning. Samantha completed her Master of Education from University of Sheffield and graduated from the National University of Singapore with a Bachelor’s in Engineering, First Class Honours. She has also completed THEC (Teaching in Higher Education) and ACTA (Advanced Certificate in Training and Assessment). She is a member of the adult associate educator (AEN) by Institute for Adult Learning (IAL), Singapore. Her certifications include: Microsoft Certified Azure Data Scientist Associate. Microsoft Certified Data Analyst Associate. SAS Certified Predictive Modeller in SAS Enterprise Miner. Tableau Certified Desktop Specialist.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Programme Fee S$2,850.00 S$2,850.00 S$2,850.00 S$2,850.00 S$2,850.00
    Less: SSG Grant Amount S$1,995.00 S$1,995.00 S$1,995.00 S$1,995.00 -
    Nett Programme Fee S$855.00 S$855.00 S$855.00 S$855.00 S$2,850.00
    9% GST on Nett Programme Fee S$76.95 S$76.95 S$76.95 S$76.95 S$256.50
    Total Nett Programme Fee Payable, Including GST S$931.95 S$931.95 S$931.95 S$931.95 S$3,106.50
    Less Additional Funding - S$570.00 - S$570.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$931.95 S$361.95 S$931.95 S$361.95 S$3,106.50
    1. Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
    2. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
    3. Please note that all external funding for courses is limited in duration and subject to eligibility and availability.

    Other Information

    This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

    Advanced Computing for Executives

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Email: soc-ace@nus.edu.sg

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