Data Science Tutorials

Master time calculations in Excel. Apply ready-to-use formulas directly to your own data.

Learn what a normality test is, why it matters, and how to use common tests like Shapiro-Wilk, Kolmogorov-Smirnov, and visual methods to check your data + examples in Python and R.

Learn how to use GPT-5.4 computer use to build a live news dashboard that automatically gathers and summarizes news.

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

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 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.