AI Key Concepts & Terms - The Missing Guide

Understand LLMs, AI agents, prompts and context engineering. Learn AI terminology in under 2 hours. No coding needed.
What you'll learn

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Explain the AI terminology you encounter every day, from machine learning and LLMs to tokens and context windows.
Describe how AI agents work, including tools, agent loops and the software that connects everything.
Make sense of model training and fine-tuning, including LoRA, synthetic data, RLHF and distillation.
Explain how prompts, context engineering and memory shape AI responses, and why longer conversations can become less reliable.
Connect grounding, RAG, embeddings and vector databases to understand how AI works with relevant information.
Distinguish MCP, agent skills and computer use, and explain what each adds to AI agents.
Recognize hallucinations, prompt injection and data exposure risks, and explain where sandboxes and human oversight help.
Look beyond headline benchmark scores: understand evals and the trade-offs behind model size, speed, cost and local deployment.
Requirements

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Start from scratch: no prior AI knowledge, programming experience or advanced mathematics required.
All you need is curiosity and a device to watch the lessons. No paid AI subscription, API key or software installation required.
Description

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Understand the language of AI-and see how the pieces fit together.
LLMs, AI agents, tokens, RAG, MCP, context engineering... These terms appear everywhere. But what do they actually mean, why do they matter, and how do they connect?
AI Key Concepts & Terms - The Missing Guide gives you the foundation to make sense of modern artificial intelligence. Move beyond recognizing buzzwords and build a clear understanding of the models, tools and systems behind today's AI applications.
Join Maximilian Schwarzmüller and build your understanding through straightforward explanations, diagrams and concrete examples. Whether you are completely new to AI or already use tools like ChatGPT and Claude, you will learn how the key concepts connect.
What you'll learn

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Make sense of AI and language models. Understand how AI, machine learning and neural networks relate. Discover what sets LLMs, smaller models and multimodal models apart.
Understand what shapes an AI response. Explore tokens, context windows, temperature, prompt engineering and context engineering. Learn why the information you provide matters.
See how models are trained and improved. Get clear explanations of training, inference, fine-tuning, LoRA, synthetic data, RLHF and distillation. Understand the ideas behind caching, quantization and model routing.
Find out how AI agents get work done. Follow the agent loop and understand the roles of tools and harnesses. Explore MCP, agent skills, computer use and human oversight.
Understand knowledge, memory and reliability. Connect grounding, RAG, embeddings and vector databases. Discover how memory, compaction and context rot affect longer interactions.
Evaluate AI claims and recognize risks. Look beyond benchmark headlines, understand evals, and learn about hallucinations, prompt injection and data exfiltration. Explore open model weights and the possibilities of running models yourself.
A clear starting point. A useful reference.
You do not need programming skills, advanced mathematics or previous AI knowledge. There is no software to install and no paid AI subscription required. The focus is on understanding the concepts through explanations and visual examples.
Most lessons take only a few minutes. Follow the full course to build a connected foundation, or return to an individual lesson when you encounter an unfamiliar term.
Whether you want to follow AI discussions, understand the tools you already use, communicate with technical teams or prepare for more specialized AI learning, this course helps you ask better questions and make sense of what you are hearing.
Join the course and turn AI buzzwords into concepts you can explain with confidence.
Who this course is for

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Beginners who want to make sense of AI buzzwords and build a clear, connected understanding of modern AI.
ChatGPT, Claude and other AI tool users who want to understand how their tools work and why results can vary.
Developers and technical professionals who want to close knowledge gaps and connect the concepts behind LLMs and AI agents.
Product managers, business professionals and team leads who want to ask better questions about AI and communicate confidently with technical teams.
Homepage

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