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Microsoft

The course introduces Microsoft 365 Copilot, covering its core features. You’ll learn how to create effective prompts and use Copilot across Microsoft 365 applications. Build a foundation in retrieving information, generating content, and streamlining tasks. Through hands-on activities and real-world scenarios, you’ll learn to integrate Copilot into your workflows to boost productivity and make informed decisions.

By the end of the course, you'll be able to:

• Explain the key concepts and capabilities of Microsoft 365 Copilot across applications like Word, Excel, and PowerPoint.

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The course introduces Microsoft 365 Copilot, covering its core features. You’ll learn how to create effective prompts and use Copilot across Microsoft 365 applications. Build a foundation in retrieving information, generating content, and streamlining tasks. Through hands-on activities and real-world scenarios, you’ll learn to integrate Copilot into your workflows to boost productivity and make informed decisions.

By the end of the course, you'll be able to:

• Explain the key concepts and capabilities of Microsoft 365 Copilot across applications like Word, Excel, and PowerPoint.

• Create effective prompts to get accurate, relevant, and creative responses from Copilot for various tasks.

• Retrieve, organize, and analyze information from different Microsoft 365 sources using Copilot's intelligent tools.

• Generate, edit, and format text content with Copilot in Microsoft Word to meet your professional needs.

• Identify ethical principles like transparency and privacy and apply best practices to ensure responsible AI use.

This course will give you the confidence to use Microsoft 365 Copilot in personal and professional settings.

Enroll now

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What's inside

Syllabus

Introduction to Microsoft 365 Copilot
In this module, you will explore the core components and capabilities of Microsoft 365 Copilot, its integration with key applications, and how to configure its basic settings for optimal use. You’ll also examine ethical AI principles, addressing challenges like bias and privacy concerns, and learn best practices for responsible AI deployment.
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Learners who complete Fundamentals of Microsoft 365 Generative AI will develop knowledge and skills that may be useful to these careers:

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Provides a simple and easy-to-follow guide to Microsoft 365 Copilot. It is written by Peter Weverka, a technology writer who has extensive experience in explaining complex topics in a clear and concise way.
Provides a hands-on guide to building custom solutions with Microsoft 365 Copilot. It is written by Jason Beres, a developer who has extensive experience in developing solutions for Microsoft 365 Copilot.
Provides a strategic guide to using Microsoft 365 Copilot to drive digital transformation in businesses. It is written by two business leaders, Mark P. Miller and Rebecca Wettemann, who have extensive experience in helping organizations use technology to achieve their business goals.
Provides a comprehensive overview of Microsoft 365 Copilot, including its features, benefits, and best practices for use. It is written by Ed Bott, a technology journalist who has extensive experience in covering Microsoft products and services.
Provides a technical deep dive into Microsoft 365 Copilot, covering its architecture, components, and configuration options. It is written by Ben Armstrong, an IT pro who has extensive experience in deploying and managing Microsoft 365 Copilot in enterprise environments.
Explores the relationship between generative AI and the creative process, discussing how generative AI can be used to enhance creativity. It is written by Margaret Boden, a leading researcher in the field.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Explores the potential applications of generative AI in healthcare, discussing how it could be used to improve patient care and accelerate drug discovery. It is written by Eric Topol, a leading researcher in the field.
Explores the potential impact of generative AI on society, discussing how it could be used to solve social problems and improve quality of life. It is written by Kai-Fu Lee, a leading researcher in the field.
Explores the potential impact of generative AI on the economy, discussing how it could be used to create new jobs and improve productivity. It is written by two leading experts in the field, Erik Brynjolfsson and Andrew McAfee.
Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
Explores the potential impact of generative AI on the law, discussing how it could be used to automate legal processes and improve access to justice. It is written by Ryan Abbott, a leading researcher in the field.
Explores the philosophical implications of generative AI, discussing how it challenges our understanding of mind and consciousness. It is written by Daniel C. Dennett, a leading philosopher in the field.
Explores the potential applications of generative AI in climate change, discussing how it could be used to model climate change and develop solutions. It is written by Andrew Ng, a leading researcher in the field.
Focuses on the use of prompt engineering for education. It is written by Salman Khan, a leading researcher in the field of education.
Covers the use of prompt engineering for finance. It is written by Richard Roll, a leading researcher in the field of finance.
Focuses on the use of prompt engineering for recommendation systems. It is written by Masashi Sugiyama, a leading researcher in the field of recommendation systems.
Focuses on the use of prompt engineering for natural language processing. It is written by Thomas Wolf, a leading researcher in the field of NLP.
For those who want to understand the mechanics of LLMs deeply, this book guides you through building one from scratch. This is highly technical and suitable for advanced undergraduate students, graduate students, and researchers. A deep understanding of LLM architecture is beneficial for advanced prompt engineering techniques.

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