Learning AI & Machine Learning
AI (Artificial Intelligence) is a field no engineer can ignore in 2026. With generative AI tools like ChatGPT, Claude, and Gemini now part of everyday workflows, understanding what AI is doing and how it works has become a real advantage for engineers.
This section covers everything from AI and machine learning fundamentals to MCP — the protocol that lets AI tools connect to external services — all in a way that builds knowledge step by step.
What I Cover Here
Section titled “What I Cover Here”Learn how AI, machine learning, and deep learning relate to each other, and understand the core concepts behind each.
- What Is Machine Learning? — How machines learn from data, and how this differs from traditional programming
- What Is Deep Learning? — How neural networks work, and an overview of LLMs (Large Language Models)
- Learning Paradigms — Transfer learning, fine-tuning, federated learning, and other modern techniques
Learn about MCP — the open standard that lets AI models connect with external tools and data. Understanding MCP explains why tools like Claude Code and Claude Desktop can integrate with so many services.
- What Is MCP? — An overview of the protocol that bridges AI and external tools
- Why MCP? — The M×N integration problem and how MCP solves it
- MCP Architecture — The three-layer structure: Host, Client, and Server
- MCP Capabilities — Tools, Resources, and Prompts — what they are and when to use each
Suggested Learning Order
Section titled “Suggested Learning Order”Starting with AI & machine learning basics
Section titled “Starting with AI & machine learning basics”Begin with What Is Machine Learning? to get a clear picture of how AI, ML, and deep learning relate before diving into each topic.
- What Is Machine Learning? — AI vs. ML, and the three types of learning
- What Is Deep Learning? — Neural networks and how LLMs work
- Learning Paradigms — Practical techniques like transfer learning and fine-tuning
Learning MCP for practical AI tool use
Section titled “Learning MCP for practical AI tool use”If you want to get more out of tools like Claude Code, start with What Is MCP?.
- What Is MCP? — Core concepts and overview
- Why MCP? — The problem it solves
- MCP Architecture — How it works under the hood
- MCP Capabilities — What you can actually do with it
Prerequisites
Section titled “Prerequisites”No advanced math is required. Having a basic sense of functions and probability from high school math will help, but it is not necessary to follow along with the conceptual explanations.
Familiarity with engineering basics (terminal, Git) is helpful but not required. Reading Engineering Basics first will give you a more practical foundation.
This page in Japanese: AI・機械学習を学ぶ