Getting Started with AWS Generative AI for Developers

Getting Started with AWS Generative AI for Developers

This course is part of AWS Generative AI and AI Agents with Amazon Bedrock Professional Certificate

Instructors: Russell Sayers

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2 modules

Gain insight into a topic and learn the fundamentals.

54 reviews

Beginner level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

54 reviews

Beginner level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Amazon Bedrock
Foundation Model Selection
Responsible AI Implementation

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

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This course is part of the AWS Generative AI and AI Agents with Amazon Bedrock Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Amazon Web Services

There are 2 modules in this course

Get introduced to generative AI with this foundational course designed for developers looking to use AWS' generative AI services. This course serves as your gateway to understanding and implementing generative AI solutions using Amazon Bedrock.

You'll begin by exploring the fundamentals of generative AI, understanding its place within the broader AI landscape, and learning key concepts such as foundation models, prompts, and inference. Through hands-on labs and demos, you'll gain practical experience invoking foundation models and interpreting their responses. The course then dives into Amazon Bedrock Runtime APIs, covering operations like InvokeModel and asynchronous invocations. You'll learn to implement streaming responses, manage provisioned throughput, and apply guardrails to ensure responsible AI use. A significant portion of the course focuses on working effectively with foundation models. You'll explore model selection criteria, learn the art of prompt engineering, and understand how to optimize your interactions with generative AI tools. By the end of this course, you'll have an understanding of generative AI concepts and hands-on experience with Amazon Bedrock. You'll be ready to start integrating AI capabilities into your applications, setting the stage for more generative AI development in subsequent courses. Please note: The hands-on exercises are optional and require access to your own AWS account. Completing these activities may result in minimal usage charges.

In this module, you will gain foundational knowledge of generative AI, including the differences between AI, machine learning, deep learning, and the role of large language and foundation models. You will explore key concepts such as prompts, inference, and responses, and see how these are practically applied using Amazon Bedrock. Through demos and hands-on labs, you will invoke foundation models to generate outputs like text, images, and code. This module also introduces Amazon Q Developer and how generative AI can enhance the software development lifecycle.

What's included

6 videos5 readings1 assignment

6 videos Total 40 minutes

Introduction to the Course 3 minutes
Amazon Bedrock for Generative AI 6 minutes
Invoking an Amazon Bedrock Foundation Model 8 minutes
Amazon Q Developer 8 minutes
Demo Amazon Q Developer CLI Vibe Coding 6 minutes
Demo Amazon Q Developer on Github 8 minutes

5 readings Total 157 minutes

Course Roadmap 2 minutes
Amazon Bedrock 15 minutes
Exercise: Invoking an Amazon Bedrock Foundation Model 60 minutes
Amazon Q Developer 20 minutes
Exercise: Debug and Generate Code with Amazon Q Developer 60 minutes

1 assignment Total 25 minutes

Module 1 Quiz 25 minutes

This module focuses on integrating generative AI into applications using Amazon Bedrock’s APIs and runtime features. You will learn to invoke foundation models using synchronous, asynchronous, and batch methods, understanding important configurations like temperature and throughput options. The module also covers choosing the right foundation model, applying prompt engineering techniques, and implementing responsible AI practices such as guardrails. You will also explore real-world developer tasks enhanced by Amazon Q Developer, such as infrastructure generation, automated documentation, and feature development.

What's included

10 videos7 readings2 assignments1 plugin

10 videos Total 77 minutes

Accessing Amazon Bedrock Runtime APIs 9 minutes
Asynchronous and Batch Inference 11 minutes
Demo Amazon Bedrock Samples Repository 2 minutes
Adding Guardrails for inputs and responses 8 minutes
Choosing a Foundation Model 6 minutes
Prompt Engineering 4 minutes
Demo Amazon Q Developer Dev Agent 8 minutes
Demo Amazon Q Developer Dev Agent Feature Dev 7 minutes
Demo Amazon Q Developer Documentation Agent 4 minutes
Tech Talk: What's possible with Generative AI? 18 minutes

7 readings Total 151 minutes

Amazon Q Developer Bedrock APIs 20 minutes
Exercise: Amazon Bedrock Guardrails 60 minutes
Responsible AI 20 minutes
Foundation Models 20 minutes
Prompt Engineering Guide 15 minutes
Glossary Course 1 15 minutes
Post-Course Survey 1 minute

2 assignments Total 85 minutes

Module 2 Quiz 25 minutes
Final Assessment 60 minutes

1 plugin Total 15 minutes

Post-Course Survey 15 minutes

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Instructors

Instructor ratings

(14 ratings)

Russell Sayers

Amazon Web Services

21 Courses 133,411 learners

Offered by

Amazon Web Services

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Reviewed on Dec 13, 2025

Excellent coaches! Congratulations to Morgan and Russ. Thank you!

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