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Coding tutorials, software development, and CS concepts
Senior developers are increasingly shipping AI-generated code, with reports showing it introduces 1.7 times more security vulnerabilities and quality issues than human-written code, creating an urgent need for stricter review processes and human oversight.
This crash course introduces FastAPI as a high-performance Python framework for building modern APIs, emphasizing fundamental concepts like ASGI architecture, Pydantic validation, and automatic documentation while demonstrating how to build a functional issue tracker API from scratch.
This tutorial explains how to extend Gemini CLI beyond local codebase interaction using MCP (Model Context Protocol) servers to connect with external APIs like Firebase, and demonstrates how to install Gemini CLI extensions that bundle MCP servers with custom commands and context files.
This tutorial demonstrates how to extend Gemini CLI by creating custom slash commands stored as TOML files in `.gemini/commands/`, enabling complex automated workflows like UI component generation with integrated testing, git branching, and preview rendering through structured multi-step prompts.
Despite fears of AI replacing entry-level developers, junior job listings have rebounded 47% since late 2023, but the bar has risen—employers now demand deep fundamentals and practical skills in high-demand languages like Python, JavaScript/TypeScript, and SQL rather than just tutorial-level knowledge.
Software development education has shifted from memorizing syntax for simple stacks like jQuery and PHP to mastering fundamental concepts while leveraging AI tools like Cursor and ChatGPT as learning assistants, requiring learners to combine structured curriculum with independent real-world projects.
The Coding Train demonstrates how to implement a Naive Bayes text classifier in JavaScript from scratch, using a concrete library book probability example to explain Bayes Theorem before coding a lightweight, browser-based word-frequency classification system.
Daniel Shiffman builds a local browser-based conversational chatbot using p5.js and Transformers.js, demonstrating how to run lightweight open-source AI models (Whisper for speech-to-text, Kokoro for text-to-speech) entirely in the browser without cloud dependencies.
Dan Schiffman outlines The Coding Train's return to regular content, detailing a sustainable workflow of converting live streams into edited tutorials, dual-path teaching strategies for p5.js 2.0 features like async/await and variable fonts, and a 2026 roadmap involving a studio move to enable physical computing.
This course teaches developers to build production-ready AI features using React and Node.js, emphasizing clean architecture and core LLM concepts over 'vibe coding,' with hands-on projects including a chatbot and review summarizer.