Generative AI Tutorials

GitHub Copilot has moved far beyond “AI autocomplete for code.” In 2026, the differences between GitHub Copilot plans come down to privacy boundaries, admin controls, auditability, and the governance your organization needs.

Learn how to build an automated LLM-as-a-judge system to evaluate your RAG pipelines for faithfulness and relevance at scale and bridge the gap in AI testing.

Learn how to run Meta's TRIBE V2 model on Google Colab, predict cortical activity from naturalistic stimuli, and visualize the results as interactive 3D brain heatmaps.

Build reliable AI apps faster by turning ad-hoc prompt checks into structured LLM evaluations with Promptfoo, from local test suites to automated CI.

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 Claude Code best practices from production teams. Use plan mode, CLAUDE.md files, and test-driven development to make the most of Claude's context window.

Learn how to use Claude Code’s Plan Mode to explore your codebase in read-only mode, surface questions, and review structured plans for multi-file changes.

Discover how to use Claude Code Router to connect to multiple providers, use the optimal LLM for every task, and reduce API cost without changing your workflow.

Learn everything you need to know about Google’s latest image generation model, Nano Banana 2, including how to build an iterative chat image editor using the API with Python.

A hands-on Python guide to ByteDance's Seedream 4.5 image model covering batch generation, text rendering, multi-image editing, and prompting best practices.

Discover Kling 3.0 and its key features. Learn how to generate videos, create your own characters, and craft complex multi-shot scenes with native audio.

Learn how to generate videos using the Grok Imagine API. This Python guide covers everything from image animations to video editing with the new xAI video model.