Foundation of Data Science

Part of the ModularMaster in Data Science (Healthcare) programme

Foundation of Data Science course offers a understanding of the end-to-end data science lifecycle, from identifying and understanding business problems to making data-driven decisions. It emphasises the importance of formulating clear objectives, collaborating with stakeholders, collecting and preprocessing data, and performing data analysis. The course also covers into simple modelling and analysis, exploring basic statistical techniques and machine learning algorithms for extracting insights. Overall, it provides essential knowledge and skills for effectively navigating the data science lifecycle and driving impactful decision-making in various industries.

This course, spanning a duration of five days, is specifically designed to equips participants with valuable skills in data analysis and communication in healthcare context. Over the first four days, participants will explore how to analyse healthcare data, perform statistical tests, and communicate important findings to different audiences. Using real-life healthcare scenarios and advanced tools, participants will develop skills to draw meaningful conclusions and contribute to evidence-based decision-making. Participants will be actively involved in a healthcare-related project throughout the module. The final day, which is split into two half-days on separate weeks, will be dedicated to project consultation and project presentation.

Plan your learning path

This course can be taken as a module on its own or as part of the Graduate Certificate in Fundamentals in Data Science (Healthcare) or ModularMaster in Data Science (Healthcare).

Course Details

Course Dates 2024:
2, 9, 16, 23, 30 Apr, 14 May


Who Should Attend

Catering to healthcare professionals and individuals aspiring to join the healthcare industry, this course is specifically designed to develop foundational knowledge and skills in data science. It is highly recommended for clinicians, administrators, and managers working within healthcare organizations to enhance their capabilities and acquire the necessary competence to become proficient citizen business or data analysts in the healthcare field.


  • Participants should preferably have passed mathematics at least ‘O’ Level or equivalent.

  • Participants should preferably have basic knowledge of statistic.

  • Participants should be conversant with basic IT skills such as software installation, file management and web navigation.

  • Participants should have basic familiarity with Microsoft Excel: using built-in functions to perform some calculations.

  • Participants are required to bring their laptops.

Programme Outline

Learning Objectives
  • Understand what is Big Data Analytics, how it is used and where it can be applied.
  • Prepare, analyse, identify business insights, and apply data science and big data analytics.
  • ​Develop, evaluate testing methods for statistical model.
  • Demonstrate through a presentation on how they have designed and applied a data analysis project from start to finish and the key results of the analysis and insights gained.
  • Understand healthcare case studies shared by SingHealth faculty members to gain insights into real-world scenarios.
  • Utilise curated public healthcare datasets to perform hands-on activities and assignments, fostering practical experience and understanding of the subject matter.
Day 1 - Introduction to data science

- Data science lifecycle
- Common tools in data science
- Roles in data science
- Data acquisition
- Types of analytics used in healthcare

Day 2 - Data Preparation

- Data profiling
- Data cleaning
- Data enrichment
- Descriptive statistics used in healthcare

Day 3 - Data science modelling

- Data validation
- Types of statistical test
- Regression and classification models

Day 4 - Data visualisation and business decision

- Visualisation and dashboard
- Data storytelling

Day 5 - Consultation/ Project presentation

Project Consultation

Each group of participants will present the progress of their projects and have the opportunity to ask questions and clarify any doubts pertaining to their projects.

Project Presentation

Each group of participants will showcase their work and respond to questions during a Q&A session.

Course Fees and Funding

Full course fee inclusive of prevailing GST

You pay

SkillsFuture Course Fee subsidy (70%)

  • For Singapore Citizens < 40 years old 
  • For Permanent Residents

You pay

Mid-Career Enhanced Subsidy (90%)

  • For Singapore Citizens ≥ 40 years old

You pay

Enhanced Training Support for SMEs (90%)

  • For SME - Sponsored employees

You pay

The above module fee payable is inclusive of 9% GST. 

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Thia Wei Soon
Instructor, SUTD Academy

Wei Soon has more than ten years of experience working in the manufacturing and IT sectors. He worked as a data scientist using data analytics and machine learning to deliver actionable insights and drive strategic marketing initiatives. In recent years, as a technology consultant, he successfully helped clients to streamline enterprise operations and achieved cost saving through the adoption of robotic process automation.

Wei Soon has a Master of IT in Business Artificial Intelligence from Singapore Management of University and a B.Eng in Mechanical Engineering from Nanyang Technological University. He is proficient with tools such as Tableau, Jupyter, RStudio, MS Visual Studio, Automation Anywhere, UiPath, and programming languages such as Python, R, C#, HTML5, and JavaScript.


Narayan Venkataraman
Assistant Director, Data Management & Informatics, Changi General Hospital

Narayan (Nari) is a Data Science and Biomedical professional with more than 22 years of experience in healthcare with diverse portfolio spanning data science, health informatics, data governance, medical technology, clinical quality and operational analytics, patient safety and risk management.
He is currently the Assistant Director, Data Management & Informatics at Changi General Hospital, Singapore. Recipient of the Singapore Commendation Medal 2022 for Covid19, he is a member of the CGH Covid19 Taskforce and many strategic committees at CGH and SingHealth (SHS). He has completed many medical projects across the Asia-Pacific region representing Singapore MOH and MFA. He is also an honorary biomed consultant for Smiles Asia and has volunteered for many surgical missions in Asia and Oceania. His current academic interests cover robotic process automation, AI/Machine Learning, data visualisation, risk analytics and enterprise data literacy.



Oh Hong Choon
Deputy Director, Health Services Research, Changi General Hospital

After earning his doctoral degree in engineering in 2009, Hong Choon has been involved extensively in operations research (OR) related studies in various public healthcare institutions in Singapore. Besides being invited regularly to give talks or conduct workshops on healthcare OR, he has received funding support for several research studies as Principal Investigator and Co-Investigator. Moreover, Hong Choon is also lead author and co-author of several peer-reviewed publications in both clinical and engineering journals. His current research interests are in the areas of optimisation under data uncertainty, discrete event simulation, predictive modeling and cost effectiveness evaluation.
As the current Head of the Health Services Research (HSR) unit in Changi General Hospital (CGH), Hong Choon leads a team of 11 analysts in projects related to data analytics, programme evaluation and health technology assessment. All these projects are primarily initiated with the ultimate goal of enabling CGH to make informed decisions or to deliver better patient care. In addition, Hong Choon also has secondary appointments as Deputy Director at SingHealth Centre for Population Health Research and Implementation and as Adjunct Assistant Professor at Duke-NUS Medical School.



Dr Jansen Koh Meng Kwang
Assistant Chairman, Medical Board (Performance Excellence) & Chief, Senior Consultant, Respiratory Medicine, Changi General Hospital

Dr Jansen obtained his MBBS from the National University Hospital of Singapore in 2001. He is the Head of Department for Respiratory & Critical care Medicine Changi General Hospital and currently the Chair of the Chapter of Respiratory Physicians, Academy of Medicine, Singapore. He heads the Center for Performance Excellence in his capacity as Assistant Chairman Medical Board, Changi General Hospital, and is the co-director for the Changi Simulation Institute. He is a Fellow at the Academy of Medicine Singapore, Royal College of Physicians Edinburgh and American College of Chest Physicians.

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In consideration of the subsidy provided by SkillsFuture Singapore Agency (“SSG”) through the SUTD Academy for the Course,

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The collection, use and disclosure to relevant third parties of my personal data by the SUTD Academy including but not limited to personal particulars, attendance records, assessment/performance records, for the following purposes:

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  3. General administration of the Course including but not limited to processing of the subsidy provided by SSG;

  4. Publicity and marketing of the Course or other Courses to be provided by SSG or SUTD Academy; and

  5. SSG or its Appointed Auditors or Nominated Representatives to directly contact Course Participant to obtain information deemed necessary for the purposes of conducting effectiveness survey or audits in relation to the Course.

I agree to:

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  1. If a written notification is sent to within 24 hours after course registration deadline there will be no cancellation charges. A full refund will be made. 

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Funding under Mid-Career Enhanced Subsidy ("MCES")

  1. MCES is an enhanced Subsidy to encourage mid-career individuals to upskill and reskill, thereby helping them to remain competitive and resilient in the job market. With this, all Singaporeans aged 40 and above will receive higher subsidies of up to 90% course fee subsidy for SSG-funded certifiable courses.

  2. Individuals/employers are not required to submit an application for the MCES. Those pursuing SSG-funded programmes will be charged the appropriate subsidised fees by SUTD Academy if they are eligible MCES. Individuals/employers will only need to pay the nett fee (full course fee after SSG's grant).

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Funding under Enhanced Training Support for SMEs ("ETSS")

  1. ETSS is an enhanced funding to enable SMEs to send their employees for training.

  2. SMEs will enjoy subsidies of up to 90% of the course fees when they sponsor their employees for SSG-funded certifiable courses.

  3. In addition to higher course fee funding, SMEs can also claim absentee payroll funding of 80% of basic hourly salary at a higher cap of $7.50 per hour. SMEs may apply for the absentee payroll via the SkillsConnect system.

  4. To qualify, SMEs must meet all of the following criteria:
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    - Employment size of not more than 200 or with annual sales turnover of not more than $100 million
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UTAP is a training benefit for NTUC members to defray their cost of training. This benefit is to encourage more union members to go for skills upgrading.

NTUC members enjoy 50% unfunded course fee support for up to $250 each year when you sign up for courses supported under UTAP (Union Training Assistance Programme).

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