Discover how Microsoft Copilot for Microsoft 365 elevates workplace 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.
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.
This course introduces fundamental 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.
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 Copilot for Microsoft 365 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.
This one-day course is composed of two parts – Getting started with Copilot for Microsoft 365 and Empower your workforce with Copilot for Microsoft 365 Use Cases. The first part of the course introduces you to Copilot for Microsoft 365, examines how you can use Copilot throughout the various Microsoft 365 apps, explores best practices for using Copilot and building effective prompts, and examines how you can extend Copilot with plugins and Graph connectors.
The second part of this training content is really the heart of this course. Students perform a series of hands-on exercises involving seven Use Cases – Executives, Sales, Marketing, Finance, IT, HR, and Operations. 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 Copilot for Microsoft 365. 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.
AI-102 Designing and Implementing a Microsoft Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.
In this course, the student will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics.
This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Finally, this course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI.
In this course students will gain the knowledge and skills needed to implement security controls, maintain the security posture, and identify and remediate vulnerabilities by using a variety of security tools. The course covers scripting and automation, virtualization, and cloud N-tier architecture.
This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms.
This course teaches Azure Solution Architects how to design infrastructure solutions. Course topics cover governance, compute, application architecture, storage, data integration, authentication, networks, business continuity, and migrations. The course combines lecture with case studies to demonstrate basic architect design principles.
