Data Science Tutorials

A practical guide to implementing Chrome’s emerging WebMCP agent interface standard with HTML, JavaScript, safety patterns, and testing workflows.

Learn how PicoClaw, the AI agent CLI under 10MB, runs on cheap hardware. This tutorial covers setup, features, real use cases, and how to get started fast.

Learn how to design and maintain a lean CLAUDE.md file, so Claude Code reliably follows your project’s rules, conventions, and workflows in every session.

Learn how polynomial approximations power gradient descent, XGBoost, and the functions your computer calculates every day.

Learn how to build and deploy powerful AI agents in Microsoft Copilot Studio. Answer questions using RAG, SharePoint integration, LLM reasoning, and tool calls.

Learn about mathematical functions: what they are, how they relate to programming functions, and how they are used in machine learning modeling.

Learn how to use Qwen 3.5 small models locally through Ollama to turn a short gameplay clip into a playable HTML game.

Spin up a no-cost BigQuery environment, practice real-world SQL on public and private data, and build dashboards while staying within generous free-tier limits.

Discover how Google's newest specialized reasoning model can accelerate your data science workflows, interpret complex datasets, and write robust code.

Break your AI coding agent out of its sandbox. Discover how to use Codex CLI and MCP to connect LLMs to live data, external tools, and multi-agent workflows.

Learn how Cursor rules guide AI coding, from defining project-level context and file-matching patterns to maintaining accurate, up-to-date rules over time.

The Laplacian operator is one of the most widely used mathematical tools in modern machine learning. It’s behind spectral clustering, manifold learning, image edge detection, and graph-based algorithms.