Tutorials

A portfolio of example agentic AI systems spanning research, software engineering, productivity and education, meant to demonstrate multi-agent collaboration and tool use.

• Tutorials

A Packt-published, hands-on course that teaches how to design, build and deploy agentic AI systems using frameworks such as Smolagents, CrewAI, MCP and n8n.

• Tutorials

End-to-end tutorials, how-to Jupyter notebooks and guides for Siemens' AI Software Development Kit, which packages, tests and creates inference pipelines for deployment on the AI Inference Server.

• Data engineering
• Tutorials

A free, open curriculum of notebooks, papers and hands-on apps that takes learners from beginner to production AI engineer over 17 weekly sessions.

• Tutorials

A Mixture-of-Experts language model implemented from scratch in native PyTorch and trained on two free Kaggle T4 GPUs, meant to teach modern LLM internals.

• Models
• Tutorials

A demonstration project showing how to build hybrid search and retrieval-augmented generation with OpenAI embeddings stored in a Pinecone vector database and orchestrated with LangChain, including a PDF-loading pipeline.

• RAG
• Tutorials

A companion HR policy question-answering example that reimplements the same guarded RAG workflow as an explicit LangGraph state graph, with visible per-node execution traces instead of a linear chain.

• RAG
• Tutorials

An HR policy question-answering example built with LangChain LCEL that classifies whether a question is in scope before retrieving from a local FAISS index, refusing to answer out-of-scope questions.

• RAG
• Tutorials

An example project that builds a question-answering system over a collection of videos, extracting frames and transcripts, embedding them into a shared multimodal space, and answering questions with a vision-language model.

• RAG
• Tutorials

Two side-by-side sample RAG (Retrieval-Augmented Generation) projects for Korea's eGovFrame standard framework, one built with Spring AI and Redis Stack and the other with LangChain4j and PostgreSQL/pgvector.

• RAG
• Tutorials

Training material that shows how to deploy and run large language models on local infrastructure such as HPC systems, including a slide deck, source code, and model and data download scripts.

• Tutorials

A bilingual, Chinese-first hands-on course that teaches AI agent development from zero to full-stack deployment, covering more than ten agent frameworks across 23-plus chapters with runnable examples.

• Tutorials

A short, guided Google Colab walkthrough for trying retrieval-augmented generation using NVIDIA's NIM cloud API, which offers free large language model inference on a T4 GPU runtime.

• RAG
• Tutorials

A hands-on, first-principles course explaining why LLM inference is memory-bound and how techniques such as batching, KV-cache management, quantization, and parallelism address it, with GPU labs building up to vLLM and SGLang.

• Inference
• Tutorials

A Microsoft sample application and workshop that builds a retrieval-augmented ChatGPT-style assistant in Java using LangChain4j, Quarkus, and Qdrant as the vector database, deployable to Azure or run fully locally with Ollama.

• RAG
• Tutorials

An AWS sample application demonstrating serverless semantic search over images and live video using Amazon OpenSearch as a vector database and Amazon Bedrock's Titan multimodal embeddings model.

• RAG
• Tutorials

A collection of 114 runnable Jupyter notebooks that each teach one prompt engineering technique, from zero-shot prompting through chain-of-thought reasoning, few-shot learning, and output formatting, across several LLM providers.

• Tutorials

A deployment and configuration guide for running Strix, an autonomous AI penetration-testing agent, on Kali Linux, covering reconnaissance, proof-of-concept generation, and multi-provider LLM setup.

• Security
• Tutorials

A technical guide documenting how to run local LLM and image-generation inference on an AMD RX 580 GPU through Vulkan, after AMD dropped ROCm support for that hardware generation.

• Inference
• Tutorials

A community study guide for the Model Context Protocol Associate certification from the Linux Foundation's Agentic AI Foundation, covering every exam domain with a weighted study plan and practice questions.

• Tutorials

A reference collection of Windows commands for system administration, security auditing and incident response, grouped into eight categories such as firewall, logs and persistence checks.

• Security
• Tutorials

A demo multi-agent travel-planning assistant built with LangGraph and MCP, showing a supervisor agent, input guardrails and human-in-the-loop approval around a FastAPI web frontend.

• Agent frameworks
• Tutorials

A collection of deployment recipes and practical guides for running the Ling model family locally with SGLang, vLLM, llama.cpp, Ollama and MLX across consumer and workstation hardware.

• Inference
• Tutorials

Forty self-contained tutorials on production retrieval-augmented generation techniques, from chunking strategies to agentic and graph-based retrieval, runnable on any OpenAI-compatible provider.

• RAG
• Tutorials