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Video course · 15 chapters · 212 min · certificate

AI Product Management Course: LLMs, RAG, AI Agents, Evaluations

AI product management fundamentals: the GenAI revolution, how LLMs are trained, transformers and GPUs, post-training and hallucinations, the AI value chain, an AI note-taker case study, context engineering, RAG, prompt engineering, fine-tuning, agents, guardrails, evaluation and building a portfolio.

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What you'll learn

  • Explain how LLMs are trained and why they hallucinate
  • Map the AI product value chain
  • Analyse an AI product case study
  • Choose between RAG, prompting and fine-tuning
  • Design agents with guardrails
  • Evaluate AI products and build a portfolio

Chapters

15 chapters · 211:51
  1. 14:04 01Intro Members AI product management and LLMs The GenAI revolution and understanding LLMs.
  2. 10:42 02LLMs Members Stages of LLM training Pre-training, training and post-training.
  3. 13:55 03LLMs Members Transformers and GPUs Parameters, transformers and why GPUs matter.
  4. 18:20 04LLMs Members Post-training, hallucinations and the value chain Reducing hallucinations and the AI product value chain.
  5. 8:53 05Case study Members Case study: AI note takers Meeting assistants: market and business value.
  6. 16:18 06Product Members How meeting tools work and growth Bots vs integrations, growth strategies, and context engineering.
  7. 16:24 07Context Members RAG Retrieval-augmented generation basics.
  8. 11:52 08Prompting Members Prompt engineering essentials Essentials and keeping a prompt library.
  9. 16:16 09Prompting Members Prompting for busy people Practical prompting and recap.
  10. 21:26 10Prompting Members Prompt techniques Simple but effective prompting tips.
  11. 10:46 11Context Members Fine-tuning and transfer learning Fine-tuning as the third part of context engineering.
  12. 15:10 12Agents Members Creating AI agents Agents like smart managers; a LinkedIn summarizer that emails.
  13. 17:10 13Safety Members Guardrails Validating inputs and outputs.
  14. 14:12 14Evals Members Evaluating AI products Challenges like hallucination and bias; a job website example.
  15. 6:23 15Career Members Building an AI portfolio Start small: content and projects.

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.

Product ManagersChief Product Officers (CPOs)AI EngineersInnovation StrategistsCTOs (Chief Technology Officers)Solutions ArchitectsAI ConsultantsCDOs (Chief Digital Officers)Software ArchitectsMachine Learning EngineersSoftware EngineersTechnology Managers