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AI Key Concepts & Terms - The Missing Guide
Welcome & AI Foundations
Welcome to the Course (1:03)
Download the Complete Course Slide Deck
Artificial Intelligence (AI) (2:24)
Machine Learning (ML) (2:22)
Neural Networks & Deep Learning (2:24)
Large Language Models (LLMs) (3:10)
Small Language Models (SLMs) (2:24)
Vision Language Models (VLMs) (1:27)
Multimodality (1:31)
Frontier Models (0:49)
Artificial General Intelligence (AGI) (1:33)
Language Models, Tokens & Context
Parameters & Weights (1:35)
Tokens (2:17)
Tokenizers & Tokenization (0:40)
The Context Window (2:48)
Context (1:43)
Temperature & Sampling (2:15)
Mixture of Experts (MoE) (1:10)
Training Models & Improving Efficiency
Training vs. Inference (1:50)
Pre-Training vs. Post-Training (2:07)
Fine-Tuning (1:41)
LoRA & Parameter-Efficient Fine-Tuning (1:38)
Synthetic Data (2:17)
Reinforcement Learning from Human Feedback (RLHF) (2:28)
Distillation (1:51)
Data Poisoning (1:51)
Reasoning Models (0:49)
Caching (1:13)
Quantization (1:59)
Model Routing (2:35)
Prompts, APIs & AI Agents
Prompts (1:09)
Prompt Engineering (1:20)
Context Engineering (1:07)
Structured Outputs (1:32)
APIs for AI Models (1:58)
Models vs. AI Agents (2:24)
AI Agents (2:18)
Tools (1:45)
The Agent Loop (2:32)
The Harness (1:26)
Knowledge, Memory & Reliable Answers
Hallucinations (1:29)
Grounding (2:10)
Retrieval-Augmented Generation (RAG) (1:40)
Vector Databases & Embeddings (2:54)
Memory (3:27)
Compaction (2:45)
Context Rot (2:53)
Agent Capabilities, Oversight & AI Coding
Model Context Protocol (MCP) (2:43)
Agent Skills (3:45)
Computer Use (2:05)
Sandboxes (2:07)
Agentic Search (1:59)
Human in the Loop (1:29)
Agentic Engineering (1:12)
Vibe Coding (1:22)
Evaluating AI, Risks & Model Choices
Benchmarks (1:42)
Evals (1:56)
Prompt Injection (2:33)
Data Exfiltration (2:21)
Open-Weights & Open-Source Models (1:28)
Reinforcement Learning from Human Feedback (RLHF)
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