💡 Generative AI & Prompt Engineering

Duration: 8 Weeks | Mode: Online | Hands-on Projects + Tool-Based Learning

🎯 Who Should Join?

• Software developers, data scientists, and ML engineers

• Product managers, QA engineers, tech leads

• AI enthusiasts and professionals looking to upskill in GenAI

• Anyone interested in building AI-powered applications and tools

📘 Course Overview

This course offers a complete, hands-on introduction to Generative AI, Large Language Models (LLMs), Prompt Engineering, LangChain, and cloud-based GenAI services. Learn to build GenAI-powered chatbots, automate content generation, fine-tune models, and deploy secure and scalable solutions using AWS, Azure, and GCP.

📚 Key Modules & Topics Covered

🔹 Module 1: Introduction to Generative AI

• Generative AI vs Traditional AI

• NLP Basics, ML vs DL vs AI

• Popular Use Cases (Content, Code, Image, Voice, Testing)

🔹 Module 2: Large Language Models (LLMs)

• OpenAI, GPT, BERT, T5, Transformers

• GANs, Autoencoders, RLHF

• Text Generation & Chatbot Concepts

🔹 Module 3: Foundation Model Architectures

• Encoder (BERT), Decoder (GPT), Encoder-Decoder (T5)

• Open Source vs Commercial Models

• GGML vs GGUF Quantization

🔹 Module 4–5: LangChain & Retrieval Augmented Generation (RAG)

• LangChain + LamaIndex Integration

• Hugging Face APIs

• Vector DBs, Semantic Search, RAG Design

• Medical Chatbot Project (End-to-End)

🔹 Module 6–8: Advanced RAG, Fine-Tuning & Evaluation

• COT, LOTR

• LoRA, Soft Prompts, PEFT Techniques

• Evaluation Metrics: BLEU, METEOR, ROUGE1, CIDEr

🔹 Module 9–13: Cloud Platforms & Deployment

• Deployment Strategies, Hardware Planning

• Generative AI on Hugging Face Hub

• AWS Bedrock, Azure Cognitive Services

• GCP Vertex AI & Gemini Pro

🔹 Module 14: Introduction to ChatGPT & GPT Architectures

• GPT-3.5 vs GPT-4

• Capabilities, Architecture, Limitations

• Ethics & Bias Management

🔹 Module 15–16: Prompt Engineering (Core + Advanced)

• Prompt Types: Zero-shot, Few-shot, Chain of Thought

• Tokens, Parameters, Creativity in Prompts

• Avoiding Hallucinations, Prompt Optimization

🔹 Module 17–18: Agents & Guardrails

• LangChain Agents, AWS Bedrock Agents

• Crew AI Overview

• Implementing Guardrails (Azure, AWS)

🔹 Module 19: GitHub Copilot for Developers

• Code Generation, Documentation & Testing

• Using Copilot in real-world workflows

• Prompting best practices for coding agents

🔹 Module 20: Generative AI for Software Testing

• Test Case Generation from Images

• Understanding & Automating Test Scripts

• GenAI-Driven QA Strategy

🔹 Module 21: Real-World Case Studies & Projects

• Build:

  • Chatbot for Medical Industry

  • NLP-to-SQL Generator

  • Chat with PDF Bot

  • Code Translation Tool

  • Gemini Pro Project

  • Self-Healing Code Demo

✅ Course Outcome

By the end of this course, you'll be able to:
✔️ Build GenAI apps using LangChain, LLMs & RAG
✔️ Craft effective prompts for text, code, and conversation
✔️ Fine-tune and evaluate foundation models
✔️ Deploy GenAI solutions using AWS, Azure, and GCP
✔️ Lead GenAI initiatives in real-world enterprise projects