Tutorials

A collection of runnable quickstarts and feature demos for the CrewAI multi-agent framework, each a self-contained Jupyter notebook or Python example meant to be extended for a developer's own project.

• Agent frameworks
• Tutorials

Sample code and a CloudFormation template for building a question-answering application with Amazon Bedrock, using a knowledge base backed by Amazon OpenSearch Serverless for retrieval-augmented generation.

• RAG
• Tutorials

A 100-day self-study challenge that links one AI or machine-learning concept per day to a companion blog post, moving from machine-learning foundations through neural-network training to AI agents in production.

• Tutorials

An example iOS Xcode project showing how to run the YOLOv5 object-detection model, converted to Core ML, on a photo picked from the device's photo library.

• Mobile
• Tutorials

A free, open-source AI and machine-learning curriculum of more than 950 hands-on Jupyter notebooks, covering Python, deep learning, large language models, retrieval-augmented generation, agents, prompt engineering, fine-tuning and MLOps.

• Tutorials

An interactive platform for learning AI and machine learning through animated visualizations and runnable browser-based Python, paired with more than twenty end-to-end example projects from classical machine learning to production LLM systems.

• Tutorials

A collection of open-source example applications showing how to build on-device AI apps with full NPU acceleration using ZETIC's Melange model-conversion platform, covering offline translation, voice and vision tasks.

• Mobile
• Tutorials

A 15-chapter, hands-on Python course that builds a coding agent's harness one primitive at a time, proving each addition against a real local model rather than mocking it.

• Tutorials

A hands-on workshop of labs that build semantic search, recommendations, retrieval-augmented generation and agentic incident remediation using pgvector, Aurora PostgreSQL and Amazon Bedrock.

• RAG
• Tutorials

A hands-on workshop that builds a multi-agent predictive-maintenance workflow for a fictitious tire factory using Microsoft Agent Framework, Microsoft Foundry and Azure.

• Tutorials

A course that teaches vector databases, embeddings and retrieval-augmented generation from fundamentals to production, working through ChromaDB, Pinecone and LangChain in runnable Python scripts.

• RAG
• Tutorials

A hands-on course that builds a retrieval-augmented-generation system from scratch in plain Python, one Jupyter notebook at a time, before showing the same pipeline rebuilt with LangChain.

• RAG
• Tutorials

A practical, hands-on guide to running large language models and coding agents locally on Apple Silicon, covering inference engine choice, memory sizing, model selection and setting up agent tool calling.

• Inference
• Tutorials

A bilingual, continuously updated course covering Claude Code and OpenAI Codex, from first installation through prompt engineering, subagents, MCP servers and full example web projects.

• Tutorials

A worked example of using AI coding assistants such as Cursor or Claude Code to build NVIDIA DeepStream SDK video analytics applications, using a curated agentic skill and structured prompts.

• Agent skills
• Tutorials

A code repository accompanying a paid course, covering LLM architecture, ChatGPT API usage, latency and cost comparisons, and hands-on Jupyter notebooks on prompt engineering.

• Tutorials

A collection of reference notes and sample code covering LLM fundamentals, retrieval-augmented generation, fine-tuning and agent frameworks, with runnable examples in LangChain, AWS Strands Agents and Google's Agent Development Kit.

• Tutorials

A TypeScript walkthrough demo showing how to build semantic search over a CSV dataset using the Pinecone vector database and a sentence-transformers embedding model.

• Databases
• Tutorials

A Chinese-language tutorial that builds an AI agent from scratch in plain Python, covering the agent loop, tools, memory and planning, before introducing frameworks such as LangChain, LangGraph and Dify.

• Tutorials

A set of self-contained Jupyter notebook tutorials introducing Hadoop, Spark and MapReduce, most runnable directly on Google Colab with no separate setup.

• Data engineering
• Tutorials

A Chinese-language interview-preparation knowledge base for AI agent engineering roles, organized around how interviews actually ask about LLM fundamentals, prompt and context engineering, RAG and tool use.

• Tutorials
• Books

Companion Colab notebooks for the Manning Publications book Domain-Specific Small Language Models, covering small-model training and optimization.

• Tutorials
• Books

Reference architectures, code examples and practice scenarios for a four-hour O'Reilly live training that prepares learners for Anthropic's Claude Certified Architect: Foundations exam.

• Tutorials

A reference handbook for engineers building production AI systems, covering reference architectures, runnable labs and interview material for a set of recurring AI-infrastructure problems.

• Tutorials
• Books