Key Takeaways
At the end of the course, you are expected to be able to:
- Design platform health metrics, operational telemetry, and forecasting systems for multi-sided environments.
- Architect and deploy real-time ML inference systems with appropriate monitoring and maintenance practices.
- Implement governance, fairness and trust/safety analytics for platform operations.
Who Should Attend
This course is suitable for:
- Early-to-mid career Data Scientists and ML Engineers responsible for operational performance and trustworthy algorithmic execution on platforms.
- Data Engineers building real-time serving, telemetry, and monitoring infrastructure.
- Product analytics or platform analytics professionals responsible for platform health measurement, forecasting, and operational decision support.
Pre-requisites
- Proficiency in Python programming.
- Working knowledge of machine learning model development and evaluation.
- Basic familiarity with cloud infrastructure or containerised deployment.
What to Bring
No printed copies of course materials are issued.
Participants must bring their internet-enabled computing device (laptops, tablet etc) with power charger to access and download course materials.
If you are bringing a laptop, please see below for the tech specs:
| Minimum | Recommended |
Operating Systems | • Windows 7, 8, 10 or
• Mac OS | Laptop running the latest
version of either Windows or
Mac OS |
System Type | 32-bit | 64-bit |
Memory | 8 GB RAM | 16+ GB RAM |
Hard Drive | 256 GB disk size | |
Others | • An internet connection – broadband wired or wireless
• Installation permissions (non-company laptops)
• Keyboard
• Mouse/Trackpad
• Display
• Power adapter (laptop battery might run out) | DirectX 10 graphics card for graphics hardware acceleration
|
Fees & Subsidies
SkillsFuture Singapore (SSG) Funding 2026 (Effective 1 July)
| Fee Component | Full Course Fees | Singapore Citizens & PRs Aged 21 Years and Above (70% Funding Support) | Singapore Citizens Aged 40 Years and Above (90% Funding Support) | Enhanced Training Support for SMEs (ETSS) (90% Funding Support) |
|---|
| Full Course Fee | S$3,800.00 | S$3,800.00 | S$3,800.00 | S$3,800.00 |
| SSG Funding | - | S$2,660.00 | S$2,660.00 | S$2,660.00 |
| Nett Course Fee | S$3,800.00 | S$1,140.00 | S$1,140.00 | S$1,140.00 |
| 9% GST on Nett Course Fee | S$342.00 | S$102.60 | S$102.60 | S$102.60 |
| Additional Funding if Eligible Under Various Schemes | - | - | S$760.00 | S$760.00 |
| Total Nett Course Fee Payable, Including GST | S$4,142.00 | S$1,242.60 | S$482.60 | S$482.60 |
|---|
Note:
- SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
- All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
- SME fees are applicable only to participants who are sponsored by small and medium enterprises.
- SSG funding is subjected to availability.
Preparing for Your Course
NUS-ISS Course Registration Terms and Conditions
Find out more.
NUS-ISS and Learner’s Commitment and Responsibilities
Find out more.
WIFI Access
WIFI access will be made available to participants.
Venue
NUS-ISS
25 Heng Mui Keng Terrace
Singapore 119615
Click HERE for directions to NUS-ISS
In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.
Course Confirmation
All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.
General Enquiry
Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.