Segment 00: Welcome to the Course: Course Overview
Segment 01: Course Introduction
Segment 02: Generative AI Impact on Engineering
Segment 03: Fundamentals of Generative AI Systems Architecture
Segment 04: Setting Up GenAI Development Environments Local _ Cloud
Segment 05: Enterprise Implementation Success Stories
Segment 06: Hands-On-Learning: Introduction to Generative AI
Segment 07: A Survey of Generative Artificial Intelligence
Segment 08: LLM Components and Core Mechanics
Segment 09: Enterprise LLM Model Comparison
Segment 10: LLM Integration and API Setup
Segment 11: Strategic Model Selection Framework
Segment 12: Hands-On-Learning: LLM Integration and API Setup
Segment 13: A Brief Survey of Large Language Models
Segment 14: Enterprise GenAI Application Matrix
Segment 15: Industry-Specific Solution Architecture
Segment 16: Support Assistant System Design
Segment 17: ROI Measurement and Metrics
Segment 18: Hands-On-Learning: Support Assistant System Design
Segment 19: Generative AI Use Cases: A Primer
Segment 20: GenAI Use Cases
Segment 21: Data Pipeline Requirements Analysis
Segment 22: Enterprise Data Pipeline Design
Segment 23: Data Processing System Implementation
Segment 24: Data Quality Validation Framework -Ritesh
Segment 25: Hands-On-Learnings: Data Processing
Segment 26: Data Preparation for Machine Learning
Segment 27: RAG System Architecture Design
Segment 28: RAG Architecture - Component Integration Fundamentals
Segment 29: RAG Implementation Best Practices-
Segment 30: RAG System Testing Protocol
Segment 31: Hands-On-Learning: RAG Fundamentals
Segment 32: Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Segment 34: Advanced RAG Pattern Analysis
Segment 35: Performance Optimization Techniques Framework
Segment 36: Complex RAG System Development
Segment 37: Enterprise Integration Best Practices
Segment 38: Hands-On-Learning: Advanced RAG: Complex RAG System Development
Segment 39: Retrieval-Augmented Generation: Recent Advances and Future Directions
