Python Syntax & Data Types Functions & OOP Concepts File Handling Exception Handling Virtual Environments & Package Management

Professional Work Culture Agile/Scrum Basics Documentation Practices Communication & Reporting

Debugging Techniques Code Review Practices Industry Coding Standards

Debugging Techniques Code Review Practices Industry Coding Standards

Generative vs Discriminative AI Tokens & Tokenization Embeddings Evolution: RNN → Transformer → LLM

Attention Mechanism Context Window Next-Token Prediction Temperature, Top-k, Top-p Sampling

Zero-shot, One-shot & Few-shot Prompting Chain-of-Thought Prompting Role-based Prompting Prompt Design Best Practices

OpenAI || Anthropic API Basics API Keys & Request-Response Structure Building a Chatbot using API Cost & Rate-Limit Awareness

LangChain Framework Introduction Retrieval-Augmented Generation (RAG) Concept Vector Databases (Basic Introduction) Building a Simple RAG-based Q&A System

Streamlit & Gradio Fundamentals Deploying Projects (Streamlit Cloud || HuggingFace Spaces) GitHub Portfolio Setup

Students are assigned a real Gen AI-based application project to build under mentor guidance

Collaborating with peers and mentors using real team workflows and version control practices

Regular code reviews to instill industry-standard coding practices and quality checks.

Breaking the project into sprints and delivering incremental features on schedule.

End-to-end development of an AI-powered feature, from design to testing and refinement.

Presenting the completed project to mentors, explaining architecture, challenges, and outcomes.

On successful completion, students receive a verified certificate with a scannable QR code confirming authenticity.