Multi-Step Retrieval Pipelines
Course Content
0 / 40 completedDevelopment Environment and Tools Setup
Components of a Production RAG Pipeline
Enterprise Use Cases for Advanced RAG
Modern RAG Architecture Overview
What is Retrieval-Augmented Generation (RAG)
Limitations of Basic RAG Systems
Re-ranking Techniques for Better Results
Metadata Filtering and Context Optimization
Hybrid Search (Vector + Keyword Search)
Understanding Embeddings and Vector Databases
Semantic Chunking Best Practices
Chunking Strategies (Fixed, Recursive, Semantic)
Handling Ambiguous and Complex Queries
Query Rewriting with LLMs
Context Expansion Techniques
Query Preprocessing Techniques
HyDE (Hypothetical Document Embeddings)
Multi-Query Generation Strategies
Multi-Step Retrieval Pipelines
Agentic RAG Workflows
Graph RAG Concepts and Knowledge Graphs
Corrective RAG (CRAG) Implementation
Multimodal RAG (Text, Images, Tables)
Self-RAG Architecture and Workflows
Security and Access Control for Enterprise Data
Observability, Logging, and Monitoring
Query Optimization
Setting Up an Enterprise RAG System
Retrieval and Generation Evaluation
Data Governance and Compliance
Course Recap
Conclusion
Future Learning Concepts
Stay up-to-Date with Communities
Enterprise Knowledge Base Integration
End-to-End Enterprise RAG Project
Common Pitfalls and Best Practices
Optimizing Latency and Throughput
Caching and Response Optimization
Scaling Large-Scale RAG Systems