Course Overview Print

Generative AI and Large Language Models (LLMs) are rapidly transforming how software applications are designed, developed, and deployed. Beyond basic interactions with AI tools, organisations are increasingly exploring how to integrate LLMs into applications, connect them to enterprise data, customize their capabilities, and develop intelligent agents that can perform complex tasks.

This course provides a practical introduction to key techniques and tools for developing LLM-powered applications. Learners will explore prompt and context engineering, LLM integration through APIs and local deployments using tools such as Ollama, Retrieval-Augmented Generation (RAG) and application development with LangChain, fine-tuning, context-aware AI agents, and AI safeguards using Guardrails AI. Through hands-on activities, learners will gain practical experience in building AI-powered solutions while addressing considerations such as accuracy, privacy, security, and responsible deployment.

 

Learning Outcomes

1. Apply prompt and context engineering, LLM APIs, local models, and RAG techniques to develop AI-powered solutions.

2. Develop AI solutions incorporating fine-tuned LLMs and context-aware AI agents.

3. Evaluate AI solutions based on accuracy, security, performance, and responsible use

Course Outline

Day 1

Morning

  1. Mastering Prompt and Context Engineering
  2. Integrating with LLMs via APIs and Local Deployments

Afternoon

  1. Building Retrieval-Augmented Generation (RAG) Pipelines
  2. Applying Fine-Tuning Strategies for Custom LLMs

Day 2

Morning

  1. ngineering Context-Aware Autonomous AI Agents
  2. Hardening LLM Pipelines with Guardrails AI

Afternoon

  1. Written Assessment
  2. Course Feedback

Target Audience and Pre-requisites

Proficient software engineers, AI developers, data scientists, and technical architects who want to transition from basic AI prompting to engineering enterprise-grade generative AI systems.

Pre-requisites

Learners should have a working knowledge of Python programming or a similar programming language, as well as access to a computer capable of running modern Python development environments and supporting local development activities for AI-enabled applications.

 

*Important Note : Fees are subject to Singapore's prevailing Goods and Services Tax (GST).
AI in Software Engineering
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