MCP
GenAI Integrations
Learn how to connect generative AI to real systems: retrieval-augmented generation over your own data, custom MCP servers that give agents safe access to your tools, and autonomous agents orchestrated to do useful work. Course Content Architecture of GenAI integrations: models, embeddings, retrieval, and orchestration Building a RAG pipeline over your own documents (vector database, chunking, retrieval) How the Model Context Protocol (MCP) works and building your own MCP server (FastAPI / Node.
SEO Tools in Practice
Run a real on-page SEO analyzer end to end: crawl a site, turn the results into actionable audits, and let AI agents propose fixes. Based on a production open-source tool built on Crawlee and Playwright, with an MCP server that exposes the whole workflow to AI agents. Course Content Running the analyzer with Docker Compose — the crawl-once, run-reports workflow What the crawler extracts: titles, meta descriptions, canonicals, hreflang, structured data (JSON-LD), broken links Reading the Markdown audit and turning issues into a prioritized developer backlog LLM-powered title and meta-description fix suggestions — and when to trust them Exposing the analyzer to AI agents via its MCP server for automated audits Formats & Pricing The same course, in three formats — pick what suits you: