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Classroom Contents
30 AI Engineering Terms Explained in Plain English
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- 1 Intro - 0:00
- 2 1 Large Language Model LLM - 0:08
- 3 2 Prompt - 0:42
- 4 3 Prompt Engineering- 1:13
- 5 4 Context Window - 2:04
- 6 5 Context Engineering - 3:25
- 7 6 Token - 3:59
- 8 7 Inference - 5:30
- 9 8 Parameter - 6:00
- 10 9 Prompt Injection - 6:52
- 11 10 Guardrails - 8:00
- 12 11 Hallucination - 8:45
- 13 12 Evals - 9:10
- 14 13 RAG - 10:11
- 15 14 Semantic Search - 10:42
- 16 15 Embedding - 12:03
- 17 16 Chunk - 13:10
- 18 17 Vector Database - 14:33
- 19 18 AI Agent - 15:01
- 20 19 Agentic AI - 15:18
- 21 20 Agentic RAG - 16:13
- 22 21 Model Context Protocol MCP - 16:47
- 23 22 Agent2Agent A2A - 18:11
- 24 23 Multi-agent System - 18:47
- 25 24 Multimodal AI - 19:36
- 26 25 Reasoning Models - 20:10
- 27 26 Fine-tuning - 20:43
- 28 27 Distillation - 21:45
- 29 28 Foundation Model - 22:04
- 30 29 Train-time Compute - 22:33
- 31 30 Train-time Compute - 22:58
