AI-ML

This learning path examines the key Microsoft 365 security and compliance features that administrators must prepare in order to successfully implement Microsoft 365 Copilot.

Do you have information locked up in structured and unstructured data sources? Using Azure AI Search, you can extract key insights from this data, and enable applications to search and analyze them.

Microsoft AI Builder offers a wide array of AI capabilities. Through this learning path, you discover how to leverage AI for your business enhancement, include text recognition, document processing automation, and incorporate AI Builder’s features into applications or workflows.

This learning path explores how the Azure AI and Azure Machine Learning Services integrations provided by the Azure AI extension for Azure Database for PostgreSQL – Flexible Server can enable you to build AI-powered apps.

In this learning path, you will learn how to create custom copilots with Copilot Studio and will get the opportunity to practice your skills in a guided project.

Discover how Microsoft Copilot and Copilot for Microsoft 365 elevates productivity and innovation. This experience, tailored for the modern business leader, provides insights on crafting contextual prompts for Copilot and includes engaging use case exercises that showcase seamless integration into daily workflows.

This training course is designed to help you understand the extensibility options available for Microsoft 365 copilot. You will learn about the different ways to extend Copilot, including building plugins and connectors, and how to choose the right option for your use case. The course also covers best practices for building high-quality plugins and connectors, as well as data, privacy, and security considerations. Whether you are a pro-code or low/no-code developer, this course will help you chart your path to extending and customizing Microsoft 365 Copilot.

Learn how to create Copilot Studio actions that extend the knowledge and capabilities of Microsoft Copilot for Microsoft 365 with external data, tailored conversations, automated flows, and custom prompts.

Discover how Microsoft Copilot for Microsoft 365 elevates workplace productivity and innovation. This experience, tailored for the modern business leader, and provides insights on crafting contextual prompts for Copilot, along with engaging use case exercises that showcase seamless integration into daily business workflows.

Learn how to use the Semantic Kernel SDK to build intelligent applications that automate tasks and perform natural language processing.

Copilots are quickly becoming a popular way to use with AI models, automate tasks, and improve productivity. In this learning path, you’ll explore options for adopting, using, and creating copilots.

In this course, business leaders find the knowledge and resources to adopt AI in their organizations. It explores planning, strategizing, and scaling AI projects in a responsible way. This course helps professionals adopt Microsoft AI solutions for their industries, and identifies AI use cases, tools, and insights from industry-specific AI success stories such as healthcare, finance, sustainability, retail, and manufacturing.

Generative Artificial Intelligence (AI) is becoming more accessible through easy-to-use platforms like Azure AI Studio. Learn how to build generative AI applications like custom copilots that use language models and prompt flow to provide value to your users.

In MS-4004: Empower your workforce with Microsoft 365 Copilot Use Cases, students perform a series of hands-on exercises involving ten Use Cases – Executives, Sales, Marketing, Finance, IT, HR, Operations, Communications, Customer Service, and Legal. These exercises focus on using Copilot in various Microsoft 365 apps (such as Word, PowerPoint, Outlook, and so on) to complete a series of common business-related tasks pertaining to each Use Case. To complete the Use Case exercises in this course, each student must have access to a Microsoft 365 subscription (BYOS) in which they’re licensed to use Microsoft 365 Copilot. Each student must also have a Microsoft OneDrive account, since Copilot requires OneDrive to complete the file sharing tasks used throughout the Use Case exercises.

Learn the knowledge and skills to drive enablement of Microsoft 365 Copilot across your organization. Explore effective strategies, including the Microsoft 365 Copilot user enablement framework to help you create and implement a robust adoption plan.

This course begins by examining the Microsoft Copilot for Microsoft 365 design. Its main focus, however, is on the security and compliance features that administrators must configure in their Microsoft 365 tenant to protect their company’s organizational data before they implement Copilot for Microsoft 365.

Discover ways to craft effective and contextual prompts for Microsoft 365 Copilot that create, simplify, transform, and compile content across Microsoft 365 applications. Learn the importance of providing a clear goal, context, source, and expectation in your prompt for the best results. This course covers real world scenarios and examples using Copilot in Microsoft 365 apps like Word, Excel, PowerPoint, Teams, Outlook, OneNote, and Chat.

To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions. Throughout this learning path, you explore how to set up your Azure Machine Learning workspace, after which you train and deploy a machine learning model.

This course is intended for software developers wanting to build AI infused computer vision applications that leverage Microsoft Foundry and Azure Vision. 

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.

This course is intended for software developers wanting to build AI infused applications that extract information in Azure, including Azure AI Content Understanding and Azure AI Document Intelligence. 

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands on activities for each topic area.

AI-102: Develop AI solutions in Azure is intended for software developers wanting to build AI infused applications that leverage Azure AI Foundry and other Azure AI services. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement computer vision and information extraction.