AWS: Generative AI & Bedrock

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

3 weeks, 2 hours a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

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Overview

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This course is designed to provide a comprehensive introduction to Generative AI and the AWS services that enable organizations to build, customize, and deploy AI-powered applications. Learners will explore the foundational concepts of generative AI, understand how foundation models work, and discover how businesses are using these technologies to transform customer experiences, automate processes, and drive innovation. The course begins by introducing the core concepts of generative AI, including foundation models, model lifecycles, business use cases, challenges, and evaluation metrics. Learners will then explore Amazon Q and Amazon Bedrock, gaining an understanding of how AWS simplifies the development of generative AI applications through managed services and access to multiple foundation models. Finally, the course covers advanced concepts such as Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and model evaluation, enabling learners to understand how modern AI applications are built and governed. This course is structured into multiple modules, each featuring lessons and video lectures that provide theoretical knowledge and practical demonstrations. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply generative AI concepts in real-world scenarios. Module 1: Generative AI Foundations Module 2: Amazon Q & Amazon Bedrock Fundamentals Module 3: RAG, Knowledge Bases & AI Agents ## At the end of the course, learners will learn * Understand the core concepts, terminology, use cases, and business value of Generative AI and Foundation Models. * Explore Amazon Q, Amazon Bedrock, and foundation model selection strategies to build AI-powered applications on AWS. * Understand Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and evaluation techniques for developing trustworthy generative AI solutions. This course is for Team Managers, Business Leaders, Cloud Practitioners, Solutions Architects, Developers, Data Engineers, AI Enthusiasts, Technical Consultants, and professionals interested in understanding Generative AI on AWS.

Syllabus

Generative AI Foundations

Welcome to the Generative AI Foundations module. In this module, you'll build a strong understanding of the core concepts behind Generative AI. We'll begin by exploring What is a Generative AI Model, along with key terminology, common use cases, challenges, and the major components that power generative AI systems. Next, you'll learn about the Lifecycle of Foundation Models, the different Types of Foundation Models, and how organizations select the right models for specific business needs. Finally, you'll explore Business Metrics for Generative AI, helping you understand how organizations measure the value, performance, and impact of AI initiatives. By the end of this module, you'll have a solid foundation in Generative AI concepts and be prepared to explore advanced AI services and applications.

Amazon Q & Amazon Bedrock Fundamentals

Welcome to the Amazon Q & Amazon Bedrock Fundamentals module. In this module, you'll explore AWS's generative AI services and learn how organizations build AI-powered applications and assistants. You'll begin with Amazon Q Business, Amazon Q Apps, and Amazon Q Developer, understanding how these services help improve productivity, automate tasks, and accelerate software development. Next, you'll dive into Amazon Bedrock, starting with an overview and demo to understand how it provides access to leading foundation models through a fully managed service. You'll also learn how to choose the right foundation model for different business use cases. Finally, you'll explore foundation model fine-tuning, evaluation metrics, PartyRock - Amazon Bedrock Playground, and Amazon Bedrock pricing, helping you understand how to customize, evaluate, experiment with, and optimize AI solutions on AWS. By the end of this module, you'll have a solid understanding of Amazon Q, Amazon Bedrock, foundation models, and key considerations for building generative AI applications on AWS.

RAG, Knowledge Bases & AI Agents

Welcome to the RAG, Knowledge Bases & AI Agents module. In this module, you'll explore how modern AI applications retrieve and use enterprise knowledge to generate more accurate and context-aware responses. You'll begin with Understanding RAG Architecture of LLMs and explore AWS Services for Storage of Vector Embeddings, learning how Retrieval Augmented Generation improves AI outputs using external knowledge sources. You'll then see these concepts in action through the Amazon Bedrock RAG & Knowledge Base Demo. Next, you'll learn how to implement responsible AI using Amazon Bedrock Guardrails, along with a hands-on demo to understand safety controls, content filtering, and governance capabilities. Finally, you'll explore Amazon Bedrock Agents, model evaluation techniques, and integrations with services such as Amazon S3 and Amazon CloudWatch, helping you understand how intelligent agents can automate workflows and interact with enterprise systems. By the end of this module, you'll understand how to build secure, scalable, and knowledge-driven AI solutions using Amazon Bedrock.