Microsoft

Leading Cross-Functional AI Delivery

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Microsoft

Leading Cross-Functional AI Delivery

This course is part of Managing AI Projects with Microsoft Professional Certificate

Microsoft

Instructor: Microsoft

Included with Coursera Plus

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Manage AI project execution using agile methods adapted for AI development.

  • Plan resources, identify risks, and maintain structured RAID tracking .

  • Use Azure DevOps to coordinate AI workstreams and stakeholder visibility.

  • Apply generative AI tools to support project documentation and communication.

Details to know

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Assessments

5 assignments

Taught in English

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Build your Leadership and Management expertise

This course is part of the Managing AI Projects with Microsoft Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate from Microsoft

There are 2 modules in this course

This module builds your ability to understand and evaluate how AI projects are structured within Azure DevOps for effective delivery oversight. You'll learn why AI projects require different organizational approaches than traditional software, particularly how to make experimentation visible, define meaningful lifecycle stages, and establish review points that support informed decision-making. By the end of this module, you'll be able to interpret AI project structures, assess whether work is organized for effective oversight, and conduct retrospectives that surface actionable improvements.

What's included

3 videos1 reading2 assignments

This module develops your ability to plan and oversee AI sprints where work includes both experimentation and delivery. You'll learn how to define sprint goals that align with learning objectives and delivery commitments, structure experimentation spikes with clear validation criteria, and interpret burndown trends when progress doesn't follow traditional patterns. By the end of this module, you'll be able to plan sprints that account for research uncertainty, recognize meaningful signals in delivery data, and make informed adjustments without overreacting to normal variability.

What's included

2 videos1 reading3 assignments

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Instructor

Microsoft
335 Courses2,602,823 learners

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Microsoft

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