Module 4.1: RAG — Retrieval Augmented Generation Explained Simply
RAG — Retrieval Augmented Generation Explained Simply
Welcome to Unit 4. In Units 1–3 you built prompt engineering skills and applied them to real work. Unit 4 goes deeper into how enterprise AI actually works — the architectures and techniques that power the AI systems being built at TCS, Infosys, Wipro, and HCL right now.
Module 4.2: AI Agents and Automation Workflows
AI Agents and Automation Workflows
In Module 4.1 you learned how RAG gives an LLM access to your documents. This module covers the next step: what happens when an LLM does not just answer a question but takes actions — browsing the web, writing and running code, calling APIs, filling forms, and coordinating with other AI systems. That is what AI agents do.
Module 4.3: Fine-Tuning vs Prompting — When to Use Which
Fine-Tuning vs Prompting — When to Use Which
You now understand prompting (Units 1–2), RAG (Module 4.1), and agents (Module 4.2). This module answers the question that comes up in almost every Indian IT AI project discussion: when is prompting enough, when should you use RAG, and when do you actually need to fine-tune?