Back to all courses
Coming Soon
RAG Systems in Production
Learn to build robust RAG systems that combine the power of retrieval with generative AI. This course covers everything from choosing the right vector database to implementing advanced chunking strategies and building reliable evaluation pipelines.
11 lessons6 hoursIntermediate
Course in Development
This course is currently being created. Follow me to get notified when it launches.
What You'll Learn
Vector database selection and optimization
Embedding models and their trade-offs
Chunking strategies for different document types
Hybrid search combining semantic and keyword search
Agentic RAG patterns with MCP integration
Production deployment and evaluation frameworks
Course Syllabus
1
Introduction to RAG30 min
2
Embedding Models Compared35 min
3
Vector Database Deep Dive45 min
4
Chunking Strategies & Optimization40 min
5
Building the Retrieval Pipeline35 min
6
Hybrid Search & Reranking35 min
7
Context Construction & Prompt Design30 min
8
Agentic RAG with MCP45 min
9
Evaluation Metrics for RAG35 min
10
Production Patterns & Optimization40 min
11
Capstone: Build an AI Knowledge Assistant50 min
Prerequisites
- •Familiarity with LLMs
- •Basic understanding of embeddings
- •Python proficiency
About the Author
PB
Pranay Bathini
Senior Software Engineer @ Booking.com
Building streaming systems at scale by day, writing about them by night. Forever learner, occasional blogger, and firm believer that the best way to understand something is to teach it.
Member of Booking Holdings India AI Committee, working on AI-powered solutions for travel at scale.