Module 1: Introduction to AI, ML & Generative AI 

• What is Artificial Intelligence — history, scope and real-world applications

• Machine Learning vs Deep Learning vs Generative AI — clear distinctions

• How Large Language Models (LLMs) work at a high level

• The GenAI landscape: tools, platforms and use cases across industries

• Setting up your AI development environment

Module 2: Python Programming Fundamentals for AI (

• Python essentials: variables, data types, control flow, functions

• Working with libraries: requests, json, os

• Understanding APIs and how AI workflows are wired together

• Reading API documentation and writing your first API call

• Hands-on: Basic Python automation scripts that talk to an AI API

Module 3: Prompt Engineering Mastery 

• What prompt engineering is and why it matters

• Zero-shot, few-shot and chain-of-thought prompting

• Designing prompts for accuracy, tone and structured output

• Common failure modes and how to debug prompts

• Prompt templates and reusable patterns

Module 4: Generative AI Tools & Text Generation 

• Tour of leading GenAI tools and platforms

• Text generation: blog posts, marketing copy, structured content

• Text summarization techniques for long documents

• Content quality control and post-processing

• Hands-on: Build an AI-based content generator

Module 5: Chatbot Development Fundamentals 

• Anatomy of a chatbot: input → context → LLM → response

• Conversation memory and context windows

• Designing personas, system prompts and guardrails

• Handling edge cases and unclear user input

• Testing your chatbot with real conversations

Module 6: AI Frameworks & API Integration 

• Introduction to popular AI frameworks for app development

• Connecting LLM APIs to your Python application

• Authentication, rate limits and error handling

• Building a simple front-end for your AI tool

• Hands-on Project: Working AI Assistant / Chatbot

Module 7: Capstone AI Project Build 

• Choose your capstone: AI Chatbot, Resume Generator or AI Study Assistant

• Project scoping, milestones and architecture

• Building the core feature loop end-to-end

• Iterating with feedback from your mentor

• Polishing the user experience

Module 8: Deployment, Demo Day & Portfolio 

• Packaging your project for sharing and submission

• Recording a clean walkthrough demo of your project

• Final project presentation to instructors and peers

• Pushing your work to GitHub and writing a strong README

• Adding the project to your resume, LinkedIn and portfolio site

Module 9: Hands-on Projects