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Amazon SageMaker helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models. SageMaker brings together a broad set of capabilities, including access to distributed training libraries, open source and foundation…

Retrieval Augmented Generation (RAG) is a powerful technique that enhances the accuracy and relevance of AI-generated responses by combining information retrieval with text generation. In this course, you will explore how to build RAG solutions…

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

This badge earner has completed all the learning activities included in this online learning experience, including hands-on experience, concepts, methods, and tools related to exploring the ethical adoption of AI technologies in the enterprise. The individual has demonstrated skills and understanding of the use of AI technologies for business, including: AI industry adoption trends, AI ethical considerations, Natural Language Processing, and Virtual Agents.

Building a Generative AI-Ready Organization is the last course in a three-part series of Generative AI Essentials for Business and Technical Decision Makers. If you have not done so already, we recommend you start with the first course in the…

This course provides components needed for successful organizational adoption of machine learning (ML). Course level: Fundamental. Duration: 30 minutes. This course includes presentations, videos, and knowledge assessments.

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some…

Learn how to decide when to use AI, combine it with other supports, and stay in control of your choices to achieve your goals effectively.

Units in this learning path:

• Introduction
• Decide AI Helpful
• Choose Another Support Needed
• Use AI Support
• Keep Supports Already Work
• Stay Control
• Try Prompts Copilot
• Practice Activity
• Knowledge Check
• Summary

Products: Power Platform, Power Apps, Azure, Azure Speech, Azure Translator Speech

Roles: Student, School Leader, K 12 Educator, Business Owner, Business Leader

Level: Beginner

Subjects: Generative AI, Business Applications, Knowledge Management, Automation, Artificial Intelligence

Duration: 18 minutes

Explore development options for extending Microsoft 365 Copilot with custom data, logic, and actions. Determine the best approach for your scenario.

Units in this learning path:

• Introduction
• Identify Extensibility Options
• Analyze Decision Criteria
• Extend Copilot Knowledge Copilot Connectors
• Build Declarative Agents Copilot Studio
• Build Declarative Agents Visual Studio Code
• Deploy Custom Agents Copilot
• Knowledge Check
• Summary

Products: Azure, Microsoft 365 Copilot, Microsoft 365 Copilot Chat, Microsoft Copilot Studio

Roles: Developer, Maker

Level: Beginner

Subjects: Generative AI

Duration: 29 minutes