| Part | Focus | Value (What You Get) | Who This Is For |
|---|---|---|---|
| Part 1 | AI Reality, Relevance & Business Impact | Clear, hype-free understanding of what AI can and cannot do in business. Aligns expectations early. | Anyone working with or affected by AI |
| Part 2 | How Modern AI Understands Information | Intuition for tokens, embeddings, context, and AI limitations. Prevents overtrust. | Anyone designing, using, or evaluating AI systems |
| Part 3 | AI & ML Fundamentals | Ability to choose between rules, ML, deep learning, and LLMs. Avoids wrong tech choices. | Product teams evaluating AI feasibility |
| Part 4 | How Models Actually Work (Systems Thinking) | Understanding AI as a system, not a black box. Better production readiness. | Product teams owning AI features |
| Part 5 | Scale, Efficiency & Tradeoffs | Early visibility into cost, latency, and performance tradeoffs. | Product teams scaling AI systems |
| Part 6 | Measuring AI & Product Success | Metrics that expose silent failures and align AI with user trust. | Product teams defining AI success |
| Part 7 | AI Product Decision Frameworks | Repeatable frameworks for deciding when to use AI and when not to. | Senior product teams & decision-makers |
| Part 8 | Model Adaptation, Retrieval & Agentic Systems | Practical understanding of RAG, fine-tuning, tools, and agents. Safer autonomy. | Product teams building advanced AI |
| Part 9 | AI in Business Functions & Operations | Where AI creates real business value vs adoption risk. | Product & business leaders |
| Part 10 | AI Product Leadership, Ethics & Lifecycle Ownership | Long-term ownership, trust, governance, and accountability. | Product, business, and AI leaders |
(Why AI matters, without hype)
(LLM-native foundations that Udemy does not go deep into)