Getting Started with AWS Generative AI for Developers

Name: Getting Started with AWS Generative AI for Developers
Rating: 4.0 (1 reviews)

Responsible AI Implementation

Created byAmazon Web Services (AWS)

Last updated 11/2025

English

What you'll learn

Demonstrate basic model invocation for Amazon Bedrock.
Identify key components of Amazon Bedrock.
Define generative AI and foundational models.
Choose and apply appropriate foundation models.

Course content

5 sections • 27 lectures • 2h 38m total length

Introduction to the Course2:35
Explore how AWS Bedrock enables developers to integrate generative AI with foundation models, prompts, and guardrails, and learn about asynchronous and batch inference for scalable apps.
Course Roadmap

Amazon Bedrock for Generative AI5:49
Explore Amazon Bedrock's serverless API access to foundation models for generative AI in applications, including LLMs, prompts, and inference for chatbots and code generation.
Invoking an Amazon Bedrock Foundation Model8:29
Explore Amazon Bedrock's generative AI via console and code using foundation models for text and image. Master prompt engineering and Bedrock API usage with Python and boto3.
Amazon Bedrock2:13
Exercise: Invoking an Amazon Bedrock Foundation Model11:11
Amazon Q Developer8:20
Discover Amazon Q Developer, a generative AI coding assistant in your IDE, offering inline code suggestions, chat help, and security scanning to accelerate AWS development.
Demo Amazon Q Developer CLI Vibe Coding6:07
Explore vibe coding with an ai assistant on the q developer cli. Build a full stack javascript whack-a-mole game using 3js and a node express backend that stores highscores locally.
Demo Amazon Q Developer on Github8:22
Demonstrates using the Amazon Q Developer GitHub app for issue-driven code generation, reviews, and Java code migration, delivering a Spring Boot Doc2FAQ prototype with file upload via a PR workflow.
Amazon Q Developer2:30
Exercise: Debug and Generate Code with Amazon Q Developer7:14
Module 1 Quiz

Accessing Amazon Bedrock Runtime APIs8:36
Discover how to use Amazon Bedrock runtime InvokeModel and response streaming, tune inference with tokens, temperature, and topP, and understand throughput and model limits.
Asynchronous and Batch Inference11:07
Explore asynchronous and batch inference with AWS Bedrock, using start-async-invoke and create-model-invocation-job to submit, track, and process text-to-video and ticket-analysis workloads via S3 inputs.
Demo Amazon Bedrock Samples Repository1:46
Explore the Amazon Bedrock samples repository on GitHub for notebooks and code snippets of the Bedrock SDK using boto3, including Bedrock APIs and the Invoke API, PoC to Prod resources.
Amazon Q Developer Bedrock APIs3:20
Adding Guardrails for inputs and responses8:11
Use Bedrock guardrails to filter harmful inputs and model responses. Configure guardrails for prompts, denied topics, and personally identifying information, with options to block or mask.
Exercise: Amazon Bedrock Guardrails7:36
Responsible AI2:53

Choosing a Foundation Model5:47
Explore how to choose and benchmark foundation models on AWS Bedrock, comparing text, image, and video modalities, cost, tokens, and API differences across providers.
Foundation Models2:19
Prompt Engineering4:28
Craft prompts iteratively to guide models, detailing the task, context, and model instructions, and control style, formatting, and outputs with examples, system prompts, and Bedrock-based retrieval-augmented generation (rag).
Prompt Engineering Guide3:05
Demo Amazon Q Developer Dev Agent7:51
Use the Amazon Q Developer agent in Visual Studio Code to generate CloudFormation templates and deployment scripts for deploying an EC2 in a private VPC.
Demo Amazon Q Developer Dev Agent Feature Dev7:10
Amazon Q Developer dev agent transforms a simple Java Spring Boot to-do app from local file storage to DynamoDB, generating repository, DynamoDB config, and related UI and tests.
Demo Amazon Q Developer Documentation Agent4:01
Use the doc agent in Amazon Q Developer to generate a README and documentation for a Spring Boot to-do app, detailing AWS infrastructure, DynamoDB, installation, deployment, and data flow.
Module 2 Quiz
Tech Talk: What's possible with Generative AI?17:47
Explore Bedrock APIs for productive ai workflows, from code-assisted development to automated internal tools. Learn how to integrate ai features into apps using multi-modal models and knowledge bases.

Requirements

AWS experience

Description

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.

Who this course is for:

Software developers with AWS experience, who are new to generative AI and eager to integrate AI capabilities into their applications.

Getting Started with AWS Generative AI for Developers

What you'll learn

Explore related topics

Course content

Introduction to the Course2 lectures • 3min

Generative AI on AWS9 lectures • 1hr

Accessing Amazon Bedrock Foundation Models7 lectures • 43min

Working with Foundation Models8 lectures • 52min

Course Wrap up1 lecture0

Requirements

Description

Who this course is for: