AI Scrum: Training and Certification in AI for Scrum (2026) | Udemy

Artificial Intelligence is no longer a future trend—it’s becoming a competitive advantage for teams that deliver products in complex and fast-changing environments. At the same time, Scrum remains one of the most widely adopted frameworks to manage uncertainty, align teams, and deliver value iteratively.

Applied AI for Scrum is a practical course designed to help you integrate AI into Scrum in a clear, structured, and responsible way—so you can improve planning, decision-making, delivery quality, and continuous improvement without losing agility.

Instead of focusing on a single tool, this course teaches AI-driven ways of working that can strengthen every part of Scrum.

What you will learn

You’ll learn how AI can support and improve:

1) Scrum Roles

• How AI enhances the work of the Product Owner, Scrum Master, and Developers
• Faster analysis, better preparation, improved facilitation, and clearer decision-making

2) Scrum Events

• Practical ways to apply AI in Sprint Planning, Daily Scrum, Sprint Review, and Sprint Retrospective
• Better alignment, earlier risk detection, more effective outcomes, and less waste

3) Scrum Artifacts

• How AI improves key artifacts such as the Product Backlog, Sprint Backlog, Increment, and User Story Mapping
• Higher-quality refinement, clearer priorities, and more consistent delivery

4) Sprints, MVPs, and Value Delivery

• How AI helps define and validate Sprints, MVPs, and product hypotheses
• How to reduce uncertainty and improve delivery execution

5) Responsible AI inside Scrum

• How to apply AI with quality, ethics, safety, and responsibility
• Common risks and anti-patterns to avoid when integrating AI in agile teams

6) Scaled Environments (Overview)

• How AI can support coordination, visibility, and decision-making in scaled agile contexts (overview)

Outcomes by the end of the course

By the end of this course, you will be able to:

• Apply AI to improve Scrum execution across roles, events, and artifacts
• Strengthen backlog quality with better refinement, prioritization, and acceptance clarity
• Improve the effectiveness of Scrum ceremonies with clearer data and better facilitation support
• Make more informed decisions and reduce delivery surprises using AI-driven approaches
• Adopt AI responsibly and avoid common misuses inside teams and organizations

Who this course is for

• Product Owners, Scrum Masters, and Agile Coaches who want to integrate AI into Scrum
• Product, innovation, and delivery professionals working in agile environments
• Tech and business professionals who want to build a competitive profile combining Agile + AI
• Students and future professionals seeking a practical, in-demand specialization

What you’ll learn

• Apply AI to improve Scrum across roles, events, and artifacts
• Improve backlog quality: refinement, prioritization, and clarity of delivery outcomes
• Enhance Sprint Planning, Daily, Review, and Retro with AI-supported decision-making
• Reduce uncertainty and improve delivery execution across sprints and MVP iterations
• Adopt AI responsibly with quality, ethics, and practical risk controls

Requirements

• Basic understanding of Scrum fundamentals (roles, events, artifacts)
• No AI or data science background required (everything is explained from a Scrum practitioner perspective)
• Willingness to apply ideas to your own team/product scenarios