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URL: https://www.coursera.org/learn/genai-for-aws-ai-driven-cloud-automation--scaling

⇱ GenAI for AWS: AI-Driven Cloud Automation & Scaling | Coursera


GenAI for AWS: AI-Driven Cloud Automation & Scaling

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GenAI for AWS: AI-Driven Cloud Automation & Scaling

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Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Describe the role of Amazon Bedrock in the AWS ecosystem and its impact on AI-driven solutions.

  • Configure and deploy generative AI models via Amazon Bedrock, integrating them into existing AWS services.

  • Design an AI-driven workflow using AWS Lambda and Step Functions.

  • Evaluate and optimize performance, security, and cost efficiency in GenAI solutions.

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Assessments

1 assignment

Taught in English

There is 1 module in this course

In this course, you’ll dive into the powerful intersection of Generative AI and cloud automation. Whether you're looking to automate cloud workflows, reduce operational costs, or deploy scalable AI-driven solutions, this course gives you the hands-on skills to do just that—using Amazon Bedrock, AWS Lambda, Step Functions, and Amazon Q. Through real-world examples, guided labs, and a capstone project, you'll learn to design, deploy, and optimize AI-powered cloud architectures that are secure, efficient, and future-ready.

This course is designed for cloud professionals and developers who want to bring generative AI into their AWS workflows. Whether you're a Cloud or DevOps Engineer looking to automate tasks with AI, an AI/ML Practitioner eager to deploy large language models via Amazon Bedrock, a Solutions Architect building scalable cloud infrastructures, or a Developer curious about enhancing applications with generative capabilities. To make the most of this course, you should already be familiar with the AWS Console and comfortable with basic cloud tasks like setting up users using IAM. Experience with core AWS services such as S3 and Lambda will be helpful, along with a basic understanding of AI/ML concepts like inference and model deployment. You should also be able to read and write simple JSON and interact with APIs. Lastly, knowledge of Python or another scripting language will help you complete hands-on activities and workflows more smoothly. By the end of this course, you'll have the confidence and technical know-how to design, deploy, and scale generative AI workflows using AWS services—unlocking new levels of automation, efficiency, and innovation. Whether you're solving real business challenges or exploring new AI capabilities, this course will give you the tools to make a real impact in your cloud projects. So dive in, experiment boldly, and let’s bring your GenAI-powered ideas to life!

In this course, you’ll dive into the powerful intersection of Generative AI and cloud automation. Whether you're looking to automate cloud workflows, reduce operational costs, or deploy scalable AI-driven solutions, this course gives you the hands-on skills to do just that—using Amazon Bedrock, AWS Lambda, Step Functions, and Amazon Q. Through real-world examples, guided labs, and a capstone project, you'll learn to design, deploy, and optimize AI-powered cloud architectures that are secure, efficient, and future-ready.

What's included

13 videos7 readings1 assignment1 peer review2 discussion prompts

13 videosTotal 69 minutes
  • Introduction and Welcome 3 minutes
  • Fundamentals of Generative AI3 minutes
  • Inside Amazon Bedrock6 minutes
  • Working with Parameters on Amazon Bedrock4 minutes
  • Configuring Bedrock for Model Deployment12 minutes
  • Serverless Inference with AWS Lambda8 minutes
  • Orchestrating Complex Workflows with Step Functions10 minutes
  • Amazon Q: Insights on Optimization and Automation5 minutes
  • Monitoring & Logging for GenAI5 minutes
  • Scaling Strategies and Performance Optimization for AI Workloads5 minutes
  • Essentials for Security and Cost Management for Generative AI Workloads in AWS 5 minutes
  • Continuous Optimization for Sustained AI Performance3 minutes
  • Congratulations and Continuous Learning Journey2 minutes
7 readingsTotal 60 minutes
  • Welcome to the Course: Course Overview5 minutes
  • 4 New Ways AWS Customers are Using Amazon Bedrock to Transform Advertising and Marketing5 minutes
  • Hands On Learning (HOL): Brainstorming and Implementing a GenAI Use Case in Amazon Bedrock20 minutes
  • Hands On Learning (HOL): Building an Automated GenAI Workflow10 minutes
  • Connecting Amazon Q and Amazon Bedrock Together5 minutes
  • Hands On Learning (HOL): Implementing Auto-Scaling & Security Configurations10 minutes
  • Well-Architected AI Lens Overview5 minutes
1 assignmentTotal 20 minutes
  • GenAI for AWS: AI-Driven Cloud Automation & Scaling20 minutes
1 peer reviewTotal 60 minutes
  • Project: End-to-End GenAI Project60 minutes
2 discussion promptsTotal 10 minutes
  • Balancing Creativity and Precision in AI Outputs 5 minutes
  • Designing Scalable AI Deployments in the Cloud5 minutes

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