AWS: Generative AI Fundamentals

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

2 weeks, 3 hours a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Part of

AWS Foundation for Senior Managers

Overview

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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 architectures, and enterprise AI best practices used in modern cloud environments. Course Modules Module 1: Basics of Generative AI Module 2: Amazon Bedrock and Generative AI Essentials By the End of This Course, You Will Be Able To: Understand generative AI concepts and foundation model fundamentals Explore business use cases and enterprise applications of generative AI Understand the lifecycle and types of foundation models Learn key concepts related to large language models (LLMs) and AI architectures Explore Amazon Bedrock and its generative AI capabilities Understand finetuning and evaluation concepts for foundation models Learn Retrieval-Augmented Generation (RAG) architecture fundamentals Explore vector embeddings and knowledge base concepts Understand Amazon Bedrock Guardrails and AI governance concepts Explore Bedrock Agents and AI application integrations Gain foundational knowledge of AWS generative AI services and enterprise AI best practices

Syllabus

Basics of Generative AI

In this module, you’ll be introduced to the foundational concepts of generative AI and foundation models used across modern enterprise AI applications. You’ll begin by exploring what generative AI is, key terminology used in AI systems, and how organizations identify business use cases for generative AI solutions. Next, you’ll learn about the challenges of generative AI, core components of generative AI systems, the lifecycle of foundation models, and different types of foundation models used across industries. The module also introduces business metrics for generative AI and explains how organizations evaluate the impact, performance, and value of AI-driven solutions. Additionally, you’ll gain foundational knowledge of modern generative AI architectures and understand how organizations apply AI technologies to improve automation, productivity, innovation, and customer experiences. By the end of this module, you’ll have a strong understanding of generative AI fundamentals, foundation models, enterprise AI use cases, and the foundational concepts required to understand modern AI systems.

Amazon Bedrock and Generative AI Essentials

In this module, the focus shifts to Amazon Bedrock, foundation model selection, RAG architectures, AI application development, and enterprise generative AI implementation concepts. You’ll explore Amazon Bedrock fundamentals and understand how organizations use Bedrock to access and deploy foundation models for generative AI applications. Next, you’ll learn how to choose foundation models, understand finetuning concepts, evaluate foundation model performance, and explore practical demos related to Amazon Bedrock. The module also introduces Retrieval-Augmented Generation (RAG) architectures, vector embeddings, knowledge bases, and enterprise AI integration concepts used to build intelligent AI-powered applications. Additionally, you’ll explore Amazon Bedrock Guardrails, Bedrock Agents, integrations with AWS services such as CloudWatch and Amazon S3, PartyRock playground environments, and Amazon Bedrock pricing considerations. Through conceptual explanations, demos, and real-world AI scenarios, you’ll learn how organizations build secure, scalable, and enterprise-ready generative AI solutions using AWS services. By the end of this module, you’ll have a strong understanding of Amazon Bedrock capabilities, AI application architectures, RAG implementations, AI governance concepts, and enterprise generative AI best practices.