Curated links for AI builders

Large language model course. From basics to RAG, agents, and fine-tuning.

Course from dlthub on building robust ELT pipelines. Includes a holiday lesson (Dec 22) on integrating LLMs into your workflow, with 50 swag packs to compete for.

Learn how to build modern, scalable data pipelines using Python and AI-assisted tools. This hands-on tutorial starts from the basics of data ingestion and takes you all the way to advanced techniques in data loading, transformation, deployment, and automation. By freeCodeCamp, featuring Alexey Grigoriev and Adrian Brudaru.

Free cohort-based version running December and January. Complete the project and review three other submissions to receive a certificate of completion signed by Alexey.

A free introductory crash course on agentic AI that explains how modern AI agents work in practice, from tools and RAG to memory, planning, MCP, and multi-agent systems. Designed as a clear, realistic starting point focused on real-world system design and limitations rather than hype.

Programming assignments for

New cohort starts on January 12, 2026. A free 9-week course on building production-ready data

Curated resource for

Materials from Tim Warner's O'Reilly Live Learning

Tutorial by Nader Dabit for building a persistent AI assistant from scratch (starting with a Telegram bot + Anthropic API) and iteratively adding sessions, memory, tool use, and scheduled tasks.

Implementation-heavy Stanford course that walks through building a language model end to

Curated list of ML resources. Frameworks, papers, and tools.

Open standard for AI coding

Curated library of real-world Claude use cases across research, writing, coding, analysis, and everyday work. Organized by role, industry, and feature with concrete, end-to-end examples.

Large open-source GitHub

Curated list of tools, patterns, and projects built around slash-command interfaces. Practical reference for command-driven workflows, bots, and developer tools.

Curated collection of AI agent use cases across healthcare, finance, education, retail, and more. Maps practical applications to open-source implementations and frameworks (CrewAI, AutoGen, Agno, LangGraph). Hands-on inspiration hub for builders and practitioners.

Practical resource that combines a live webinar recording with the full planned write-up and a demo project. It also compares the AI Engineer role to traditional data team roles and maps modern AI projects to CRISP-DM.

In-depth tutorial from Pinecone's FAISS learning series that covers LSH (theory + Python implementation) for approximate nearest-neighbor search.