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SkillsFuture Career Transition Programme (SCTP)

(SCTP) NUS Data Intelligence and Business Analytics Programme

TGS Code: TGS-2023035551

Programme Structure


Course NameCourse ScheduleMode of DeliveryTGS Reference Number
(SCTP) Using Business Analytics to Answer Business Questions3 and 6 July 2026 | 9 am - 5.30 pmSynchronous e-LearningTGS-2024046917
(SCTP) Descriptive Analytics22 to 24 July 2026 | 9 am - 5.30 pmClassroom LearningTGS-2024046836
(SCTP) Applied Analytics Using Predictive Modelling27, 31 July and 3 August 2026 | 9 am - 5.30 pmClassroom LearningTGS-2024046918
(SCTP) Python Programming7, 13 and 14 August 2026 | 9 am - 5.30 pmClassroom LearningTGS-2024046835
(SCTP) Prescriptive Analytics – From Data to Optimal Course of Action21 August 2026 | 9 am - 5.30 pm Classroom LearningTGS-2024046834
(SCTP) Trisector Strategy and Innovation for Transformation (Problem Setting)26 August 2026 | 9 am - 5.30 pmClassroom LearningTGS-2024046833
(SCTP) Trisector Strategy and Innovation for Transformation (Data Collection and Analysis)28 August, 2 September and 3 September 2026 | 9 am - 5.30 pmClassroom LearningTGS-2024046837
(SCTP) Trisector Strategy and Innovation for Transformation (Idea Generation and Strategy Consolidation)9 to 11 September 2026 | 9 am - 5.30 pmClassroom LearningTGS-2024046832
  • Please click on the individual courses for more details.
Applicants are required to register for all eight SCTP courses as part of this programme.

Programme Overview

In this dynamic landscape, we can position ourselves by staying up to date with emerging technologies and continuously improving our data-driven decision-making abilities.

The NUS School of Computing (SOC) offers the Data Intelligence & Business Analytics Programme as a suite of short courses to prepare trainees for job roles such as Business Analyst, Data Analyst, Data Architect, or Associate Data Engineer. Throughout the programme, students will gain an understanding of the analytical techniques and tools used in data science and learn how to apply these tools to projects. By the end of the programme, students will have the ability to interpret business specifications, turn insights into creating business value for organisations, and contribute to their organisation’s growth and success.

The Data Analytics Programme consists of 8 modules:

Programme Objectives

This programme will equip the participants with the following skills:

  • Understand Business Intelligence
  • Understand the functionalities of PowerBI for Business Intelligence
  • Learn the tools and techniques to perform data preparation
  • Understand how to make use of tools to perform data exploratory analysis
  • Understand how to embark on a data mining project
  • Understand the fundamental key concepts of various predictive analytics techniques
  • Acquire basic proficiency in popular data analytics tools such as R
  • Build a strong foundation in the fundamentals of Python programming
  • Learn to use libraries such as Numpy and pandas in the Python API
  • Understand how to model business problems for optimisation, interpret sensitivity analysis and shadow prices
  • Problem Setting, Data Collection and Analysis and Idea Generation and Consolidated Strategy

Job Role Readiness

  • Business / Intelligence Analyst
  • Data Analyst

Prerequisites

General Diploma

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Funding Available

  • SkillsFuture Funding
  • SkillsFuture Credit

    • Instructors


    A/Prof Danny Poo

    A/Prof Danny Poo

    Dr Danny Poo brings over 40 years of expertise in Software Engineering, Information Technology, and Management. He has been actively involved in research and consultancy in areas such as Big Data Analytics, Information Management, and Healthcare Analytics. A highly regarded speaker at industry seminars, Dr. Poo has also led numerous in-house training sessions and provided consultancy services to organisations both locally and regionally. Dr Poo is the author of several influential books on topics including Object-Oriented Software Engineering, Java Programming, Enterprise JavaBeans, Python Programming, and Computer Programming and Algorithms with Python. His extensive teaching credentials include specialised knowledge in:
    • Data Strategy
    • Data Storytelling and Visualization
    • Big Data Analytics
    • Machine Learning and AI
    • Enterprise Digital Transformation and AI
    • Data Management, Governance, and Architecture
    • Software Engineering
    • Information Technology Project Management
    • Health Informatics and Healthcare Analytics
    • Healthcare Informatics Leadership

    Dr Lek Hsiang Hui

    Dr Lek Hsiang Hui

    Dr Lek Hsiang Hui is a Specialist in Data Analytics, System Analysis and Development. He is an IT techie who is passionate about computer systems and technology. He is involved in a few startups and is constantly looking into innovative IT solutions which can be translated to business ideas, with the recent one in the area of Big Data Analytics. He is also a mobile application developer and has produced more than 10 mobile apps. Dr Lek has been teaching various undergraduate courses and executive courses in National University of Singapore (NUS) since 2006. Some of these modules include programming methodology, enterprise system analysis and development, and data mining. During this period, he has won a number of teaching awards such as NUS Annual Teaching Excellence Award (2015/16, 2016/17, 2017/18) and NUS Annual Teaching Excellence Honor Roll (2018/19), Faculty Teaching Excellence Award (2014/15, 2015/16, 2016/17), and Faculty Teaching Excellence Award Honor Roll (2017/18). Dr Lek received his Doctor of Philosophy (Information Systems) from NUS in 2013. His research area is in Natural Language Processing (Sentiment Analysis). He graduated with a Bachelor’s Degree (1st class Honors) in Computer Engineering from NUS. Industry Credentials Shopping Malls (UOL, Marina Square, ION), Healthcare (SingHealth), Government (STB), various SMEs in F&B, Apparels, Cleaning Solutions, Photography, Health Products, Baby Products.

    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.

    Dr Prakash Chandra Sukhwal

    Dr Prakash Chandra Sukhwal

    Prakash Sukhwal is a Senior Lecturer in the Department of Information Systems and Analytics at National University of Singapore. He obtained his Ph.D. in Information Systems and Analytics from School of Computing in 2024. Prior to his current role, he was a Principal Data Scientist in manufacturing industry, where he utilised his machine learning and GenAI skills to drive innovation. With over nine years of teaching experience, Prakash has taught extensively to both university graduates and industry professionals, covering courses from basic to advanced analytics. His research interests include the use of large language models, health informatics, knowledge graphs, and conversational AI. He has published in top-tier journal and conferences, such as PNAS, ICIS, HICSS, PACIS, and AAAI, and has received the NUS Research Achievement Award twice, in 2020 and 2022.

    Dr Vivek Sundar Magesh

    Dr Vivek Sundar Magesh

    Dr Vivek Sundar Magesh is a Lecturer in the Department of Information Systems and Analytics at the National University of Singapore (NUS) School of Computing. He holds a PhD in Management (specialising in Quantitative Marketing) from NUS, an MBA, and a foundational background in Electrical Engineering. His research focuses on Quantitative Marketing, Social Media, New Product Diffusion and Developing Economies. An experienced educator, Dr Magesh has taught a wide array of courses, including financial and marketing analytics, platform business models, and data visualisation. His academic work is deeply informed by his prior experience in corporate managerial positions, enabling him to provide high-level insights that bridge the gap between technical rigor and strategic business application.

    Programme Fees


    Singapore Citizens Singapore PRs
    39 years old or younger 40 years old or older
    S$5,575.35 S$2,165.35 S$5,575.35
    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 for all short courses in order to be eligible for SSG funding.
    3. The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SSG funding guidelines as of course commencement.
    4. Applicants are required to register for all eight SCTP courses as part of this programme and must complete all eight courses during this intake.
    5. Please refer to our Terms and Conditions page for more information.

    Other Information

    The SkillsFuture Career Transition Programme (SCTP) helps mid-career individuals build industry-relevant skills to boost employability and transition into new sectors or roles. Interested in learning more about the SCTP? Explore the FAQ to find answers to common questions, including programme details, eligibility criteria and funding.