Key Takeaways
By the end of the course, you will be able to:
- Apply AI effectively across the Software Development Life Cycle (SDLC)
- Generate high-quality, reliable code using structured prompting
- Move from ad-hoc prompting to repeatable engineering workflows
- Design AI agent pipelines with validation and human oversight
- Use specifications and constraints to control AI outputs
- Integrate AI into team workflows with testing, review, and governance
Who Should Attend
- Software Engineers and Developers
- DevOps and Platform Engineers
- Technical Leads, Architects, and Engineering Managers
Pre-requisites
- Basic programming knowledge (e.g., Python, JavaScript, or similar)
- Familiarity with software development concepts
- No prior AI or Machine Learning (ML) experience required
What to Bring
No printed copies of course materials are issued.
Participants must bring their laptops (participants will not be able to complete the workshop with their tablets) with power charger to access and download course materials.
If you are bringing a laptop, please see below for the tech specs:
| Minimum | Recommended |
Computer and processor | 1.6 GHz or faster, 2-core Intel Core i3 or equivalent | 1.8 GHz, 2-core Intel Core i3 or equivalent |
Memory | 4 GB RAM | 8 GB RAM |
Hard Disk | 256 GB disk size | |
Display | 1280 x 768 screen resolution (32-bit requires hardware acceleration for 4K and higher) | |
Graphics | Graphics hardware acceleration requires DirectX 9 or later, with WDDM 2.0 or higher for Windows 10 (or WDDM 1.3 or higher for Windows 10 Fall Creators Update). | DirectX 10 graphics card for graphics hardware acceleration |
Others | An internet connection – broadband wired or wireless Speakers and a microphone – built-in or USB plug-in or wireless Bluetooth A webcam or HD webcam - built-in or USB plug-in | |
What Will Be Covered
- Fundamentals of Generative AI and Large Language Models (LLMs)
- Prompt engineering for structured and predictable outputs
- AI-assisted development across SDLC phases
- Code quality, validation, and testing strategies
- Specification-driven development
- AI agent concepts and multi-step workflows
- Context management and integration with development tools
Fees & Subsidies
Fees for 2026
| | Full Fee | Singaporeans & PRs
(Self-Sponsored) |
| Full course fee | S$1,800.00 | S$1,800.00 |
| ISS Subsidy | - | S$180.00 |
| Nett Course Fee | S$1,800.00 | S$1,620.00 |
| 9% GST on Nett Course Fee | S$162.00 | S$145.80 |
Total Nett Course Fee Payable, Including GST | S$1,962.00 | S$1,765.80 |
Note:
- All fees and subsidies are valid from January 2024, unless otherwise advised.
- From 1st January 2024, the GST will be increased to 9%.
- For corporate run, please contact us directly for further details.
Certificate
The ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course and pass the required assessments.
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.