Analytics for Better Health

Ready to advance further? This course is part of the Graduate Certificate in Health Informatics.

Course Information

Dates: 15 January – 16 April 2026, every Thursday

Time: 6pm – 9pm (SGT)

Venue: MD1 Tahir Foundation Building, National University of Singapore (map)

SSG Course Code: TGS-2020507482

Overview

This course aims to introduce the data analytics techniques that are commonly needed for healthcare data and healthcare problems. We will investigate the unique challenges and considerations of implementing data analysis for healthcare problems. This will be followed by a focus on developing predictive models for various healthcare applications. We will cover the commonly used predictive machine learning models, their learning mechanisms and methods to picking the most suitable model. In the second half of the course, we will focus on the conduct of causal inference studies with retrospective healthcare data. Various causal inference techniques will be introduced.

Learning Outcomes

At the end of the course, participants will be able to:

  1. Evaluate analytics results to determine their impact on business value in the healthcare sector
  2. Elaborate the key elements to build a successful healthcare analytics solution.
  3. Summarise the common data source in healthcare
  4. Outline the commonly used data collection, data cleansing in healthcare analytics techniques.
  5. Analyse the key problems and challenges in the healthcare clinical analytics area.
  6. Apply the concepts and techniques to conduct causal inference studies with retrospective healthcare data

Who Should Attend?

Professionals in the health industry.

Entry Requirements

  • Bachelor’s degree
  • Relevant public health related work experience
  • Prior knowledge of statistics/ biostatsitcs is required
  • Candidates with other qualifications and experience may be considered on a case by case basis, subject to approval

Assessment & Certification

This is a SkillsFuture Singapore (SSG) approved course. As part of SSG funding requirements, participants have to achieve at least 75% attendance and pass all assessment(s)/examination(s).

An electronic certificate will be issued to all participants who complete the course:

  • Certificate of Competence – Attain a ‘C’ grade or above and meet a minimum of 75% attendance
  • Certificate of Participation – Attain a grade lower than ‘C’ and meet a minimum of 75% attendance

Course Instructors

Feng Mengling
Assistant Professor Feng Mengling

Dr Feng’s research is to develop effective data analytics and Artificial Intelligence (AI) solutions to extract actionable knowledge to improve the quality of care. His research brings together concepts and tools across machine learning, optimization, signal processing, statistical causal inference and big data management. In particular, he has been publishing on physiological signal forecasting, modeling of disease progress trajectory, dynamic patient phenotyping, statistical understanding of treatment effects and management of heterogeneous medical big data. Dr Feng works closely with clinicians around the world, and he also collaborates with major healthcare and IT companies, such as MSD, Philips and SAP. Dr Feng’s work was recognised by both well-established journals, such as Science Translational Medicine, JAMA, Intensive Care Medicine and top international conferences, such as KDD, AAAI and AMIA.

View his full profile here.

Course Fee

Subsidy available Fee payable after subsidy*
International Participant – S$5886.00
Singapore Citizen aged 39 years & below / Permanent Resident SSG Funding S$1765.80
Singapore Citizen aged 40 years & above SSG Funding & Mid-Career Enhanced Subsidy S$685.80
Singapore Citizen / Permanent Resident Sponsored by SMEs SSG Funding & Enhanced Training Support for SMEs S$685.80

Remarks:

  • All enrolled candidates will also be required to pay a Student Services Fee of S$25.70*.
  • Self-Sponsored participants can use their SkillsFuture Credits to pay for or offset course fees. SkillsFuture Credit claim has to be submitted to SkillsFuture Singapore (SSG) within 60 days before course commencement. SSG will not allow claims to be made after the first day of the course.
  • The University reserves the right to review and adjust the course fees and make changes to the programme structure and requirements as necessary and accordingly without prior notice.

*Prices stated above are inclusive of 9% GST. 

Application

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