AI Tutorials
Practical AI tutorials for developers
Learn AI through focused tutorials covering inference, local assistants, RAG apps, prompt workflows, model selection, and production deployment. This hub is ready to grow as you add more AI tutorials.
Complete RAG Tutorial for Developers
Learn retrieval-augmented generation from beginner concepts to production: chunking, embeddings, vector databases, retrieval, prompts, citations, code examples, RAGAS evaluation, and deployment.
Open tutorialGPU Tutorial for AI Developers
Learn GPU hardware, memory hierarchy, execution, CUDA basics, and framework layers that shape AI performance.
Open tutorialAI Inference Tutorial
A chapter-based learning path for serving models, choosing hardware, understanding runtimes, and moving toward production inference.
Open tutorialBuild a Local AI Assistant on an 8GB GPU
Create a practical local assistant with conservative memory settings, clear scope, and realistic quality checks.
Open tutorialDeploy a Small RAG App End-to-End
Build a small retrieval app with clean ingestion, tuned retrieval, grounded answers, and production monitoring basics.
Open tutorialGPU tutorial
Learn GPUs for AI workloads
Follow the GPU learning path when you want to understand VRAM limits, throughput, CUDA execution, and why different models behave differently on real hardware.
Start with inference
Learn how model serving works before choosing providers, GPUs, or deployment frameworks.
Build real AI apps
Move from concepts to small projects such as local assistants, RAG apps, and prompt-driven workflows.
Make better decisions
Use tutorials alongside model comparison, GPU planning, and deployment checklists.
All AI tutorials