Master vector databases for AI applications. Learn embeddings, similarity search, and hands-on setup of Pinecone, pgvector, and Chroma. Understand indexing strategies, hybrid search, performance optimization, and how to choose the right database for your use case.
17 módulos • 17 aulas
Build a private, offline knowledge base over your own notes and PDFs using a local AI model. A hands-on beginner micro course: run a model with Ollama, turn documents into embeddings, store them in a local Chroma database, and ask questions answered from your own files. No cloud APIs, no fees, your data stays on your machine. Want to deploy it as a web app instead? See the Full-Stack RAG course (/courses/fullstack-rag-nextjs-supabase-gemini).
Master database internals, indexing, and schema design for modern AI applications. Learn how SQL databases power production AI systems at TikTok, Uber, and Netflix. Build RAG systems, feature stores, and high-performance pipelines with PostgreSQL and pgvector.
Master the Model Context Protocol (MCP) - Anthropic's open standard for connecting AI assistants to external tools and data sources. Learn to configure, use, and build MCP servers that extend AI capabilities with real-world integrations.
Learn to leverage Claude AI for effective code review in 30 minutes. Master prompts for finding bugs, security vulnerabilities, and refactoring suggestions with hands-on practice.
Master the principles, architecture, and core components required to build production-ready RAG applications. Learn to create custom knowledge chatbots using Next.js, Supabase with pgvector, and Google's Gemini API. Perfect for JavaScript/Next.js developers who want to integrate advanced AI features.
Master the art of chaining AI prompts and building sophisticated workflows. Learn to design multi-step AI pipelines, handle errors gracefully, implement branching logic, manage context, and build production-ready AI workflows for research, content creation, and code generation.