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 lecciones
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 linear algebra through the lens of artificial intelligence. Learn vectors, matrices, dot products, eigenvalues, and tensors by seeing exactly how they power neural networks, transformers, embeddings, and other AI systems.
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.
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 probabilistic foundations of artificial intelligence. Learn probability fundamentals, Bayes' theorem, distributions, expected value, maximum likelihood estimation, and how AI systems handle uncertainty to make predictions.
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.