Do I need to complete Course 1 before taking this course?

Course 1 (AWS Generative AI and Foundation Models) provides helpful background on Bedrock, RAG, and the Rust SDK, but is not strictly required. If you are comfortable with the AWS console and understand foundation model concepts, you can start here.

Will I write real code or just use the console?

Both. The course starts with console exploration and comparison tools, then progresses to building Bedrock APIs with Bash curl scripts and the AWS SDK for Rust. You also use CloudShell for programmatic knowledge base creation.

What are Bedrock agents and why should I learn about them?

Bedrock agents are autonomous AI systems that plan and execute multi-step tasks by combining foundation models with external tools via Lambda functions. They represent the next evolution beyond simple API calls, enabling applications that reason, retrieve, and act independently.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

AWS Intelligent Applications with Amazon Bedrock

This course is part of AI Tooling Specialization

Instructors: Alfredo Deza

Included with

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Navigate the Bedrock console, compare models like Claude and Haiku, and implement patterns for cloud-to-local model portability with Ollama
Build Bedrock APIs in Bash and Rust, and create programmatic knowledge bases with S3 data sources via the console and CloudShell
Construct autonomous Bedrock agents with action groups, Lambda integration, and knowledge-base-backed RAG for grounded multi-step task execution

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the AI Tooling Specialization

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

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

There are 3 modules in this course

Learn to build intelligent applications with Amazon Bedrock through hands-on console exploration, API development, and autonomous agent construction. You will navigate the Bedrock model catalog, compare foundation models like Claude and Haiku side by side, and implement the Dracula pattern for cloud-to-local model portability using Ollama as a fallback. The course progresses from console-based prototyping to programmatic API development, where you build Bedrock clients in both Bash with curl and Rust with the AWS SDK. You will create and query knowledge bases backed by S3 data sources and Titan embedding models, using both the console and AWS CloudShell for programmatic management. The final module covers Bedrock agents — autonomous systems that plan and execute multi-step tasks using action groups, Lambda integration, and knowledge-base-backed RAG for grounded responses. By completing this course, you will be able to evaluate trade-offs between managed cloud models and local inference, build production Bedrock APIs, and construct agent workflows that combine reasoning with retrieval.