What Does a Data Management Specialist Do?
October 1, 2024
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Instructors: Starweaver Instructor Team
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Intermediate level
Basic knowledge of AWS services, AI/ML concepts, JSON, and Python is recommended to get the most out of the hands-on projects in this course.
Recommended experience
Intermediate level
Basic knowledge of AWS services, AI/ML concepts, JSON, and Python is recommended to get the most out of the hands-on projects in this course.
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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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.
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