Tutorials

A hands-on curriculum of notebooks for building autonomous, stateful, goal-driven multi-agent systems on LangGraph, progressing from foundational concepts to multi-agent orchestration.

• Tutorials

A collection of official examples and guides for building and deploying generative AI applications and agents on IBM's watsonx platform, covering several common agent frameworks.

• Agent frameworks
• Tutorials

A free, openly licensed engineering book and companion course on building and running large language model systems, covering tokenization, serving and fine-tuning models rather than only calling a hosted API.

• Tutorials
• Books

A step-by-step guide to building a personal knowledge base out of plain markdown files, using Claude Code to ingest clipped articles into an Obsidian vault that links new material to what exists.

• Tutorials

A companion set of computational notebooks, exercises and projects for the "No Bullshit Guide to Statistics" book, meant to be run in JupyterLab rather than only read.

• Tutorials
• Books

A short set of tutorials on using machine-learning methods for causal inference.

• Tutorials

A four-layer, self-paced roadmap that takes a Java developer from programming fundamentals through JVM and Spring internals to an AI-engineering track built on Spring AI, RAG, agents and MCP.

• Tutorials

A companion code repository for a beginner tutorial video and blog that builds a university FAQ chatbot on Amazon Bedrock step by step, from a first Converse API call through tool use, retrieval-augmented generation, guardrails, and a full agent built with the Strands Agents SDK.

• Tutorials

A four-hour, hands-on course that builds a complete AI nutrition-assistant agent with OpenAI's Agents SDK, covering tool calling, retrieval-augmented generation, the Model Context Protocol, multi-agent orchestration, memory, guardrails and cloud deployment.

• Tutorials

A comprehensive Chinese-language tutorial on deploying large language models locally, covering how transformer inference and quantization work, choosing hardware, and comparing deployment tools such as LM Studio, Ollama, llama.cpp, vLLM and TensorRT-LLM.

• Tutorials

An educational project that trains a large language model from scratch through two pipelines: a native C++ engine for data ingestion, tokenization and training, and a Python pipeline using Apple's MLX framework that scales a decoder-only GPT model to 1.6 billion parameters.

• Models
• Tutorials

A hands-on workshop repository for building, testing and deploying single-agent and multi-agent Hosted Agents to Microsoft Foundry Agent Service, entirely from Visual Studio Code, using the Microsoft Foundry extension and the Python Agent Framework.

• Tutorials

A progressive, curriculum-style collection of scripts and notebooks for fine-tuning Hugging Face Transformers models, moving from the high-level Trainer API down to a hand-written training loop, tokenizer details, and methods such as LoRA and prefix tuning.

• Models
• Tutorials

A white-box, self-hosted platform for learning and inspecting retrieval-augmented generation, showing the whole pipeline: document ingestion, chunking, embedding, vector and BM25 retrieval, prompt assembly and citation tracing, backed by its own benchmark data.

• RAG
• Tutorials

A short visual explanation of how attention works in transformer models, written for students trying to build an intuitive picture of the mechanism.

• Tutorials

An eighteen-notebook course that measures each component of the recursive loop behind an AI coding agent, such as verification and state persistence, with reproducible numbers on real benchmarks.

• Tutorials

A set of fifteen executable AI-assistant skills that walk a developer through finding, evaluating and submitting their first open-source contribution, across several coding assistants.

• Agent skills
• Tutorials

A structured, searchable learning path covering retrieval-augmented generation, embeddings, vector search, agents and Model Context Protocol, aimed at engineers who build with LLM APIs rather than train models.

• Tutorials
• Books

A step-by-step, freely available class that teaches data analysis with Python and Jupyter notebooks, aimed at journalists and other newcomers to programming.

• Tutorials

A curated collection of over two hundred deep-dive tutorials that explain the internal architecture of AI agents, LLM frameworks, coding tools and other open-source developer platforms.

• Tutorials
• Curated lists

A course and code repository that teaches how to build autonomous AI agents from scratch in Python using ReAct prompting, without relying on third-party agent libraries.

• Tutorials

A video-based, project-driven course bridging machine-learning theory and production AI-engineering practice, covering agentic systems, retrieval-augmented generation, orchestration, and fine-tuning large language models.

• Tutorials

A day-by-day tutorial series covering Python from basic syntax through object-oriented programming, exception handling, multithreading and data analysis with NumPy and Pandas, in a structured, beginner-friendly path.

• Tutorials

A set of educational Jupyter notebooks that teach the core patterns behind tools like Claude Code and Cursor's agent mode by having the learner build an agentic harness, a small language model and an MCP server from first principles.

• Tutorials