When Your Course Notes Earn 929 GitHub Stars

What it does This repository hosts the companion materials for a Portuguese-language postgraduate course in Software Engineering with Applied AI. It is organized into modules that collect reference links, articles, and small example projects covering LLMs, browser-based machine learning, prompt engineering, and developer automation tools.

The interesting bit The repo functions as a curated index rather than a single codebase, yet it has drawn 929 stars. That suggests it resonates beyond the classroom as a roadmap for the applied AI engineering landscape, from TensorFlow.js games to local Ollama deployments.

Key highlights

• Heavy focus on browser-based AI, including TensorFlow.js, WebGPU LLMs, genetic algorithms, and reinforcement learning experiments that run locally
• Practical MCP modules covering Playwright test generation, automated browser navigation, Grafana telemetry, and Context7 documentation lookup
• Surveys the AI-assisted development tooling landscape, comparing Cursor, Windsurf, and GitHub Copilot
• Includes local LLM deployment examples using Ollama and discussions of open-source versus proprietary model trade-offs
• Hands-on projects such as browser-based neural recommendation systems and Duck Hunt-playing bots

Caveats

• This is fundamentally a course companion and reference collection, not a standalone library or framework
• The main README is largely an annotated link directory; runnable code is scattered across example folders with sparse top-level explanation
• Some modules are still reference lists awaiting deeper implementation

Verdict Useful as a broad, structured index for Portuguese-speaking developers exploring how to ship AI features. Skip it if you are hunting for a single, production-grade tool.