Begin your AI journey by understanding fundamental concepts and ethical considerations of artificial intelligence in the cloud. This course introduces you to AI technology, focusing on how different models work and their practical applications. You'll learn to distinguish between Large Language Models (LLMs) and Foundation Models (FMs), understand responsible AI practices, and gain hands-on experience with Amazon PartyRock. Through practical exercises and real-world examples, you'll develop essential prompt engineering skills and learn how AI can enhance productivity across various job roles. The course concludes with an exploration of key AWS AI services, including Amazon Bedrock, Q Developer, Q Business, and SageMaker, providing you with a solid foundation for AI solution development.
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AI Fundamentals and the Cloud
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This module introduces AI and focuses on how to use it responsibly. You learn about the differences between Large Language Models (LLMs) and Foundation Models (FMs), including private and public models. Along the way, you discover how AI works, how it's trained on data, and the basics of machine learning. Additional topics include the impact of AI on privacy, fairness, decision-making, and prompt engineering.
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This module walks you through getting started with PartyRock. This service is able to handle much more than just text prompts, and you get a chance to see this in action. You view a demo of PartyRock, showcasing how to use chat prompts, generate images, and create widgets or applications. Thereās also a hands-on exercise where you build an application using PartyRock.
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This module covers several Amazon AI tools. You learn about Amazon Bedrock and how it helps developers build and scale generative AI applications. Next, you explore Amazon Q Developer and Amazon Q Business, and how they can be used to create and solve business challenges. Finally, you dive into Amazon SageMaker AI, learning how it can help data scientists deploy machine learning models at scale.
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å·²äŗ Oct 16, 2025å®”é
The only thing keep this from being yet another excellent AWS offering are disconnects between the Lab Instructions and the Current State of the AWS Management Console
å·²äŗ Jun 27, 2025å®”é
I have gained a lot of skills through these courses. Well design and presented in a simpler format.
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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.
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.
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