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Master object-oriented design in Rust by translating Python OO patterns—dataclasses, ABCs, mixins, and design patterns—into idiomatic Rust using structs, traits, generics, and enums.
Master generative AI on AWS, from Amazon Bedrock fundamentals to deploying serverless multi-model systems, covering security, orchestration, agentic AI, and SaaS development with Rust and Python.
Master the fusion of agile methodologies and AI tools—from sprint planning and Five Whys to AWS Bedrock, RAG, and AI pair programming—to ship real projects efficiently.
Master building production-grade ETL pipelines in Rust with type-safe extraction, error handling, and testing to prevent silent data loss and runtime panics.
Master Linux on a Framework Laptop — from hardware assembly to a fully configured Kubuntu desktop, terminal fluency, KDE Plasma customization, and LibreOffice proficiency.
Master Rust from scratch — covering ownership, borrowing, error handling, generics, traits, and lifetimes, culminating in a capstone CLI project with clean, idiomatic code.
Master building production-grade AWS Lambda functions in Rust with Cargo Lambda, comparing runtimes across Python, Ruby, and Node.js, and optimizing serverless performance through real benchmarks.
Master Zig for systems programming—build static binaries, choose the right allocator, and know when Zig beats Rust for Lambda, edge, and embedded targets.
Explore AI ethics from a human-first perspective, tracing digital rights, surveillance capitalism, and propaganda patterns to build a critical-thinking toolkit for resisting hype and advocating externality-first solutions.
Explore five Rust GUI frameworks—iced, FLTK, GTK4, relm4, and egui—by building eight real apps on Linux, from a calculator to a Pong game, and learn to ship production-ready binaries.
Master Linux terminal skills from zero — set up a free cloud environment, learn bash/zsh/sh shells, navigate filesystems, and build real command-line workflows without any local installation.
Master privacy-conscious AI development by integrating secure coding practices, vulnerability scanning, and AI assistants like Claude Code and Gemini CLI to protect production applications.
Master prompt architecture and advanced NLP on Amazon Bedrock, covering token processing, versioned prompt templates, chain-of-thought agents, and custom Rust NLP tools for production deployments.
Master building an AI-powered code review bot with GitHub Actions, using LLMs to automate pull request feedback, from prompt engineering to GitHub Marketplace publishing.
Learn to systematically debug software by combining AI tools with test-driven development, covering pattern recognition, context gathering, structured logging, and a unified workflow to find and fix bugs efficiently.
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