AI Jargon Buster: Plain English Explanations

AI conversation is full of terms that get used without explanation: LLMs, RAG, embeddings, temperature, agents, fine-tuning, MCP. This course cuts through the jargon with plain-English explanations of the terms you actually encounter, what they mean in practice, and why they matter.

beginner · 38m · 4 modules

1. Model and Training Terms

LLM, parameters, training data, fine-tuning, RLHF, foundation models, and the terms that describe how AI models are built.

• Model and Training Terms Explained, text, 5 min
• More Model Terms: Benchmarks, Alignment and Safety, text, 4 min
• Modules 1 and 2 Quiz, quiz, 3 min

2. Interaction and Behaviour Terms

Prompt, context window, temperature, hallucination, grounding, and the terms that describe how you interact with AI and what it does.

• Interaction Terms: Prompts, Context and Behaviour, text, 5 min
• More Interaction Terms: Chain of Thought, Multimodal and More, text, 4 min

3. Technical and Architecture Terms

RAG, embeddings, vector databases, APIs, tokens, inference, and the terms from AI system design and deployment.

• Technical Terms: RAG, Embeddings and APIs, text, 5 min
• More Technical Terms: Inference, Serverless and Deployment, text, 3 min

4. Industry and Business Terms

Agents, MCP, multimodal, open source, AI safety, responsible AI, and the broader terms in the AI industry conversation.

• Industry and Business Terms, text, 5 min
• Modules 3 and 4 Quiz, quiz, 3 min