You’ll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you’ll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images.

• Apply generative AI to your business use cases
• Determine which generative AI models are best suited to your task
• Perform prompt engineering and in-context learning
• Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA)
• Align generative AI models to human values with reinforcement learning from human feedback (RLHF)
• Augment your model with retrieval-augmented generation (RAG)
• Explore libraries such as LangChain and ReAct to develop agents and actions
• Build generative AI applications with Amazon Bedrock

• # Cloud Computing (Books)