AI & ML · 10hBeginnerTop PickGenerative AI FoundationsMental models for GenAI: transformers, foundation models, prompting, evals, multimodal, and responsible use.Lessons13 lessons1. What Is Generative AI?Generative AI creates new content by modeling probability over tokens, pixels, or audio — not by retrieving a single stored answer.2. Why GenAI Matters for EngineersWhy GenAI Matters for Engineers — practical lesson inside Generative AI Foundations.3. From NLP Pipelines to TransformersFrom NLP Pipelines to Transformers — practical lesson inside Generative AI Foundations.4. Attention, Context Windows & MemoryAttention, Context Windows & Memory — practical lesson inside Generative AI Foundations.5. Pretraining Objectives ExplainedPretraining Objectives Explained — practical lesson inside Generative AI Foundations.6. Foundation Models: Capabilities & LimitsFoundation Models: Capabilities & Limits — practical lesson inside Generative AI Foundations.7. Tokenization & EmbeddingsTokenization & Embeddings — practical lesson inside Generative AI Foundations.8. Prompting That Works in ProductionProduction prompting is specification writing: role, constraints, output schema, examples, and stop conditions.9. Fine-Tuning vs RAG: Decision FrameworkRAG injects fresh knowledge at request time; fine-tuning changes model behavior. Most enterprise apps should try RAG first.10. Evals, Quality Bars & Failure ModesEvals, Quality Bars & Failure Modes — practical lesson inside Generative AI Foundations.11. Multimodal GenAI BasicsMultimodal GenAI Basics — practical lesson inside Generative AI Foundations.12. Ethics, Safety & GovernanceEthics, Safety & Governance — practical lesson inside Generative AI Foundations.13. Career Map: Builder vs Operator vs LeaderCareer Map: Builder vs Operator vs Leader — practical lesson inside Generative AI Foundations.