Module 1.1: What is Generative AI — LLMs Explained Simply
What is Generative AI — LLMs Explained Simply
You have probably used ChatGPT, Copilot, or Gemini by now — maybe to draft an email, explain a bug, or summarise a document. But do you know what is actually happening when you type a message and the AI responds?
Module 2.1: Anatomy of a Good Prompt
Anatomy of a Good Prompt
Welcome to Unit 2. In Unit 1 you built a mental model of what GenAI is and where it fails. Now you start using it effectively.
Module 3.1: GenAI for Developers — Code Generation, Debugging, and Documentation
GenAI for Developers — Code Generation, Debugging, and Documentation
Welcome to Unit 3. You now have the prompt engineering skills from Unit 2. This unit is about applying those skills to your actual work — starting with the role most of you are entering or preparing for: software development.
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 5.1: GenAI Certifications Worth Getting in 2026
GenAI Certifications Worth Getting in 2026
Welcome to Unit 5 — the final unit. You have completed all the technical foundations of this course. This unit is about converting that knowledge into career outcomes: the right certifications, a strong profile, freelancing opportunities, and a final project that pulls everything together.
Generative AI: Zero to Job-Ready
A free, self-paced course designed for Indian engineering students and freshers. No maths, no jargon, no prior experience needed.
Module 1.2: ChatGPT vs Claude vs Gemini — Which to Use When
ChatGPT vs Claude vs Gemini — Which to Use When
In Module 1.1 you learned that all three tools — ChatGPT, Claude, and Gemini — are built on Large Language Models that predict the next word. So if they all work the same way under the hood, why does it matter which one you use?
Module 2.2: Zero-Shot, Few-Shot, and Chain-of-Thought Prompting
Zero-Shot, Few-Shot, and Chain-of-Thought Prompting
In Module 2.1 you learned the six components of a well-structured prompt. This module teaches three specific techniques that sit on top of that foundation — the highest-impact methods professional prompt engineers use every day.
Module 3.2: GenAI for Analysts — Data Summarisation, Reports, and Insights
GenAI for Analysts — Data Summarisation, Reports, and Insights
In Module 3.1 you saw how developers use GenAI for code generation and debugging. This module is for the other half of every Indian IT team — the analysts, business analysts, and data analysts who work with data, reports, dashboards, and stakeholder communication every day.
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.