## 1. Generative AI Uses Cases, Fundamentals, And Project Life Cycle ## 2. Prompt Engineering And In-Context Learning ## 3. Large-Language Foundation Models ### Large-Language Foundation Models ### Tokenizers ### Embedding Vectors ### Transformer Architecture ### Types of Transformer-Based Foundation Models ### Pretraining Datasets ### Scaling Laws ### Compute-Optimal Models ## 4. Memory And Compute Optimizations ## 5. Fine-Tuning And Evaluation ### Instruction Fine-Tuning ### Instruction Dataset ### Instruction Fine-Tuning ### Evaluation ## 6. Parameter-Efficient Fine-Tuning ## 7. Fine-Tuning with Reinforcement Learning From ## 8. Model Deployment Optimizations ## 9. Context-Aware Reasoning Applications Using RAG And Agents ## 10. Multimodal Foundation Models ## 11. Controlled Generation And Fine-Tuning With Stabel Diffusion ## 12. Amazon Bedrock: Managed Service For Generative AI ### References - https://learning.oreilly.com/library/view/generative-ai-on/9781098159214/ -