Master Production RAG Systems

Building RAG The Right Way

Learn to build production-grade Retrieval-Augmented Generation systems from scratch. Master evaluation, optimization, and real-world deployment patterns used by top companies.

6 Weeks

Intensive Hands-On

1 Capstone

Real Dataset Project

∞ Access

Lifetime Updates

rag_system.py

RAG Architecture

from rag_builder import RAGSystem

rag = RAGSystem()

rag.add_documents(data)

rag.evaluate_and_improve()

# Production ready ✓

6-Week Curriculum

Each week builds upon the previous, combining theory with hands-on implementation

Week 1

Starting the Flywheel

→Synthetic data
→Metrics design
→RAG fundamentals

Week 2

Evaluation to Enhancement

→Embedding fine-tuning
→Re-ranking
→Capability development

Week 3

UX Design

→Interface design
→Feedback loops
→Iterative improvement

Week 4

Query Understanding

→Query classification
→Topic modeling
→Pattern discovery

Week 5

Multimodal & Structured

→Multiple content types
→Metadata filtering
→Text-to-SQL

Week 6

Architecture & Deployment

→Intelligent routing
→Tool integration
→Production deployment

Capstone Project

Build a complete RAG system with the WildChat dataset, covering data exploration, vector database integration, synthetic generation, evaluation suite, and production deployment.

Vector DB Integration

Complete Test Suite

Performance Optimization

What You'll Master

Hands-On Learning

Practical projects and real-world scenarios. No theory-only lectures.

Modern Stack

Work with OpenAI, Anthropic, Cohere, LanceDB, ChromaDB, and production tools.

Community Support

Learn with peers, share projects, and grow together in our community.

Production Ready

Deploy with confidence. Learn optimization, streaming, and monitoring.

Technologies Covered

Master the complete modern RAG stack

LLM APIs

• OpenAI GPT Models

• Anthropic Claude

• Cohere Embeddings

Vector Databases

• LanceDB

• ChromaDB

• Turbopuffer

Evaluation & Tools

• Braintrust

• Pydantic Evals

• Logfire Monitoring

Ready to Master RAG?

Join developers and AI engineers learning to build production-grade RAG systems