RAG Systems
Build production-ready Retrieval-Augmented Generation systems with advanced chunking, hybrid search, reranking, and quality control. Master the patterns that power enterprise AI knowledge bases.
Estimated Time: 5-7 days Difficulty: Advanced Prerequisites: Modules 1-10 (especially Data Layer and APIs)
Set Up Your First RAG Environment
Install LlamaIndex or LangChain, set up a vector database (Pinecone or Weaviate), and create a simple embedding pipeline. Test it with a small document collection to understand the basic flow.
Completion Checklist
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Your Learning Path
Foundations of a Modern AI Operator
Foundations of a Modern AI Operator
Operator Mindset
Understanding LLMs
Security & Ethics
AI-Powered Content Creation & Media Systems
AI Operator Tool Primer
Core Interface Tools
Data Layer
Automation Layer
APIs & Webhooks
RAG Systems
AI Agents
Payments & Authentication
Monitoring & Logging
Product Building Track
Consulting & Business Skills
Final Portfolio Requirements
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Prerequisites
- • Module: 01-foundations
- • Module: 02-operator-mindset
- • Module: 03-understanding-llms
- • Module: 04-security-ethics
- • Module: 05-ai-content-creation
- • Module: 06-tool-primer
- • Module: 07-core-interface-tools
- • Module: 08-data-layer
- • Module: 09-automation-layer
- • Module: 10-apis-webhooks