Artificial Intelligence–Augmented Software Development Life Cycle: From Copilots to Agentic Pipelines

Build reliable software with AI from assistants to agent-driven workflows

Overview

Reference No	TGS-2026063167
Part of	-
Duration	2 days
Course Time
Enquiry	Please contact ask-iss@nus.edu.sg for more details.

Artificial Intelligence (AI) is transforming how software is built across the Software Development Life Cycle (SDLC). While AI coding assistants are widely used today, many teams struggle with code quality, reliability, and governance.

This course focuses on how to apply AI in a structured, engineering-driven way, not just generating code, but ensuring it is correct, maintainable, secure, and production-ready.

You will learn how to evolve from AI Assistants to AI Agents.

The course emphasises software engineering fundamentals, so that AI becomes a reliable part of your development process.

This course is part of the Software Systems series offered by NUS-ISS.

Upcoming Classes

Class 1: 23 to 24 July 2026
Duration: 2 Days
When: 23 & 24 Jul 2026
Time: 9:00am to 5:30pm

Class 2: 24 to 25 September 2026
Duration: 2 Days
When: 24 & 25 Sep 2026
Time: 9:00am to 5:30pm

Registration Instructions

Self-sponsored Participants

Register for the course by clicking on the "Register Now" button above
You may refer to the User Guide for Learner

Company-sponsored Participants

You will have to be registered for the course by someone from your company who has an account on the LifeLong Learning Portal (L³AP)
The person in-charge may register you for the course by:
- Generating a corporate registration link for you to register for the course
  - After the link is generated, you must:
    1. Click on the corporate registration link after logging in
  - If you do not follow the above instructions, you will be registered for the course as self-sponsored
- Registering you for the course backend
  - You will still be required to log in to L³AP and complete your registration by clicking on the "Register Now" button above
You may refer your HR/L&D POC to the User Guide for Company

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.

Course Resources

Develop your Career in the Following
Training Roadmap(s)

Please click on the discipline(s) to view the training roadmap of related courses to assess your training needs and goals.

Architecting the backbones of smart cities

NUS-ISS /
Course

Scrolltop

More than one Google Analytics scripts are registered. Please verify your pages and templates.