History and Evolution of Generative AI - Foundations: Probability, Bayesian Inference, Neural Networks -Core Architectures: GANs, VAEs, Transformers - LLM Architecture: Embeddings, Tokenization, Attention Mechanisms. Practical 1. Implement a DCGAN (Deep Convolutional GAN) for MNIST digit generation 2. Building Transformer Blocks from Scratch 3. Experimenting with Pre-trained LLMs (e.g., GPT-2, BERT) using Jupyter Notebooks.

Diffusion Models: Principles and Architectures (DDPM, Stable Diffusion) -Advanced Transformer based Models (GPT, T5) -Multimodal Generative Systems (CLIP, DALL-E, Vision-Language Models) -Model Evaluation Metrics -Safety, Bias, and Hallucination Mitigation. Practical 1. Implementing a Denoising Diffusion Probabilistic Model (DDPM) 2. Image Generation with Stable Diffusion 3. Building a Simple Multimodal (Text-to-Image) Application

Principles of Prompt Engineering -Prompt Types and Patterns (Zero-shot, Few-shot, Chain-of Thought) - Advanced Techniques: Self-Consistency, Generated Knowledge, Tree of Thoughts - System Prompts and Persona Design - Guardrails and Output Control. Practical 1. Building a Library of Effective Prompts for Various Tasks (Text Summarization, Code Generation, Creative Writing) 2. Implementing Chain-of-Thought Prompting for Complex Reasoning 3. Creating and Optimizing System Prompts for Specific Domains and Image Generation Tasks.

Definition and Characteristics of AI Agents - Agent Design Patterns and Frameworks (ReAct, LangChain, LlamaIndex) - Core Components: Planning, Tool Use, Memory, and Reflection Introduction to Multi-Agent Systems: Communication and Coordination. Practical 1. Building a Simple Tool-Using Agent with LangChain 2. Implementing a ReAct Agent for a Web Search Task 3. Designing an Agent with Memory for Conversational Context

Advanced Agent Frameworks (AutoGen, LangGraph, CrewAI) - Agentic Retrieval-Augmented Generation (RAG) -Autonomous Task Execution and Workflow Automation - Application Case Studies: AI in Education, Business Process Automation, Healthcare, and Financial Analytics Practical 1. Building a Research Assistant Agent using AutoGen 2. Creating a Workflow Automation Agent with LangGraph 3. Developing an Advanced Agentic RAG System for Domain-Specific Queries