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Video course · 15 chapters · 44 min · certificate

AI & LLM Essentials: 20 Core Concepts in 40 Minutes

Twenty core AI terms every engineer should know: LLMs, tokenization, vectors, attention, self-supervised learning, transformers, fine-tuning, few-shot prompting, RAG, vector databases, MCP, context engineering, agents, RL, chain of thought, reasoning, multimodal and small models, distillation and quantization.

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What you'll learn

  • Explain how LLMs process text
  • Understand attention and transformers
  • Compare fine-tuning, few-shot prompting and RAG
  • Explain vector databases, MCP and context engineering
  • Understand agents, RL and reasoning models
  • Know multimodal, small models, distillation and quantization

Chapters

15 chapters · 43:34
  1. 1:28 01Basics Members Large language models What an LLM is.
  2. 2:47 02Basics Members Tokenization and vectorization Breaking text into tokens and vectors.
  3. 3:07 03Architecture Members Attention The breakthrough that changed the industry.
  4. 4:45 04Training Members Self-supervised learning The 2017-era breakthrough.
  5. 2:25 05Architecture Members Transformer Transformer versus LLM.
  6. 2:33 06Training Members Fine-tuning Adapting a model for specific behaviour.
  7. 3:28 07Techniques Members Few-shot prompting and RAG Examples in prompts and augmenting queries.
  8. 2:30 08Infrastructure Members Vector databases Finding relevant documents.
  9. 2:40 09Infrastructure Members Model Context Protocol Connecting LLMs to tools and data.
  10. 3:36 10Agents Members Context engineering and agents Putting it together; agents.
  11. 5:23 11Training Members Reinforcement learning Training models to behave in particular ways.
  12. 1:54 12Reasoning Members Chain of thought and reasoning models Step-by-step thinking and reasoning models.
  13. 1:45 13Modalities Members Multimodal models Models that accept and create images and video.
  14. 2:03 14Efficiency Members Small language models Smaller models for privacy and cost.
  15. 3:10 15Efficiency Members Distillation and quantization Building small models and compressing them.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

Innovation StrategistsChief Product Officers (CPOs)CIOs (Chief Information Officers)FoundersCTOs (Chief Technology Officers)Product ManagersStrategy ManagersAI ConsultantsCDOs (Chief Digital Officers)Chief Digital Officers (CDOs)CMOs (Chief Marketing Officers)Directors of Strategy