AWS: Generative AI Fundamentals

The AWS – Generative AI Fundamentals course is designed for business leaders, senior managers, cloud professionals, developers, AI enthusiasts, and decision-makers who want to build a foundational understanding of generative AI concepts, foundation models, Amazon Bedrock, and enterprise AI applications within AWS environments. This course introduces learners to the fundamentals of generative AI and explains how organizations use AWS generative AI services to improve innovation, automate workflows, enhance customer experiences, and accelerate business transformation initiatives. You will explore core generative AI concepts including foundation models, large language models (LLMs), generative AI use cases, model evaluation, finetuning, responsible AI considerations, and Retrieval-Augmented Generation (RAG) architectures. The course also introduces Amazon Bedrock and its capabilities for building and deploying generative AI applications using foundation models from multiple providers. You’ll learn how organizations select foundation models, implement guardrails, integrate AI services, and use vector embeddings and knowledge bases for enterprise AI solutions. Additionally, learners will gain practical insights into Amazon Bedrock integrations, AI application architectures, evaluation metrics, Amazon Bedrock Agents, PartyRock playground environments, and pricing concepts used in modern generative AI solutions. Through conceptual explanations, demos, and business-focused examples, this course provides a strong foundation for understanding how generative AI technologies and AWS AI services support innovation, intelligent automation, and enterprise transformation. The course delivers approximately 5+ hours of structured video content, organized into two modules. Each module includes quizzes and knowledge checks to reinforce learning and validate understanding. Enroll in this course to gain foundational knowledge of generative AI, foundation models, Amazon Bedrock, RAG