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Short Course

Communicating Insights with Data Storytelling

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
21, 24 and 25 March 2025 | 9 am - 5.30 pm3Classroom LearningTGS-2022011489

Course Overview

With the increase in the availability of data, organizations are now grappling with the problem of how to use these data effectively for their business. Data Analytics is the practice of using digital data for understanding insights from data. To unlock the potential contained within data, it is essential for organizations to apply techniques to explore and convey key insights. That is, to tell the story within insights gleaned from data. Well-told data stories are change drivers within any institution. How to connect the data to the key underlying business issues? This course discusses the art and science of data storytelling, techniques for visualising data and the approach to telling compelling stories using data insights for effective and efficient communication.

Course Objectives

Course will enable participants to:

  • Understand and apply visualisation techniques and information displays to convey data and findings.
  • Learn how to produce effective and efficient data visualisations.
  • Organise the presentation of data to reflect trends and correlations in a visually compelling way.
  • Present effective data storytelling.

Job Role Readiness

Data analysts and health informaticians.

Prerequisites

At least a diploma (or equivalent) with managerial exposure.

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This programme is part of

  • Professional Certificate in Data Strategy and Storytelling
  • Professional Certificate in Healthcare Analytics and Storytelling

    • Types of Available Fundings

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

    • Testimonials


    This course is insightful for healthcare providers because now, we better understand how IT can complement healthcare providers to enhance patient care, and can hopefully work with informatics teams or in informatics teams to bring those enhancements to reality.

    Materials (step by step) and training for this course is easy for me to understand.

    Wong Shimin Desiree

    Instructors


    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 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.

    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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