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There are 3 modules in this course
Accelerate your AI expertise by diving deep into AWS AI services and solution architecture. This course guides you through evaluating and implementing AWS AI services for tasks ranging from generative AI to computer vision. You'll experiment with generative AI on Amazon Bedrock, learn prompt engineering techniques, and learn how AI agents can automate workflows. The course emphasizes practical application, teaching you to design effective AI architectures and integrate various AWS services for storage, databases, data processing, and security. Through hands-on labs, you'll learn to make solid decisions about AI implementation and develop the skills to architect AI solutions.
In this module, you explore the fundamentals of artificial intelligence (AI) and how AWS makes AI adoption easier through pre-trained services. You gain insight into real-world applications of AI and learn about AWS purpose-built tools for language processing, computer vision, generative AI, and more. Through hands-on examples and guided explanations, you understand how to start using these services and apply them across various business needs.
What's included
6 videos3 readings1 assignment
Show info about module content
6 videos•Total 28 minutes
Welcome to the Course•4 minutes
AI Fundamentals and AWS Services•3 minutes
Purpose-built AI Services on AWS and their Categories•5 minutes
Further Exploring Amazon Q•6 minutes
Computer Vision with Amazon Rekognition•4 minutes
Text Analysis with Amazon Comprehend•7 minutes
3 readings•Total 35 minutes
Course Roadmap•5 minutes
A Guide to Amazon Q Products•15 minutes
Overview of AWS AI Services•15 minutes
1 assignment•Total 20 minutes
Module 1 Quiz•20 minutes
Module 2: Optimizing FMs with Amazon Bedrock
Module 2•3 hours to complete
Module details
In this module, you learn how to innovate with generative AI using Amazon Bedrock by exploring prompt engineering, model customization, and task automation. You gain hands-on experience crafting effective prompts and tuning model parameters to optimize AI output. The module also introduces AI agents and outlines how to automate complex tasks using Bedrock’s advanced capabilities.
In this module, you explore the key considerations involved in designing and deploying effective AI solutions on AWS. You learn when to use pre-built AI services versus building custom models, and how to optimize cost, performance, and infrastructure. The module also covers the importance of high-quality data, AWS data services, and best practices for architecting scalable and sustainable AI systems.
What's included
6 videos4 readings2 assignments1 plugin
Show info about module content
6 videos•Total 29 minutes
Introduction to Module 3•2 minutes
Considerations for Corporate AI solutions•5 minutes
Data Services for AI Solutions•7 minutes
Architecting AI Solutions•4 minutes
Tech Talk: AI Architecting Best Practices•9 minutes
Course Closing•3 minutes
4 readings•Total 41 minutes
Data Foundations•15 minutes
Additional Resources•10 minutes
Course 2 Glossary •15 minutes
Post Course Survey•1 minute
2 assignments•Total 70 minutes
Optimizing AI Workloads on AWS•30 minutes
Final Assessment•40 minutes
1 plugin•Total 15 minutes
Post Course Survey•15 minutes
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Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence, security, hybrid and enterprise applications, from 44 Availability Zones across 16 geographic regions. AWS services are trusted by millions of active customers around the world — including the fastest-growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs.
Coursera and AWS have been partners since 2017 providing learners and enterprises globally, the skills they need to succeed. Coursera builds on AWS servers to scale with student demand with confidence around capacity and elasticity and in partnership with AWS. In 2019, Coursera achieved Advanced Tier Partner status and further extended the partnership with AWS Educate, AWS EdStart and AWS Academy collaborations.
Coursera's been able to make cloud skills more accessible with 8 AWS courses on the Coursera platform featuring top subject matter experts and the portfolio continues to grow.
To learn more about AWS, visit https://aws.amazon.com.
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Learner reviews
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J
JT
4·
Reviewed on Oct 24, 2025
You have got some very good stuff. Just organize the courses a little better - longer and more structured on the core services and less of an encyclopedia of everything you have got.
G
GT
5·
Reviewed on Jul 2, 2025
Oksana is just a wonderful person, I really enjoyed her speech
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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 Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, 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.