In this module, you will be introduced to foundational knowledge about the Product Backlog. You will also learn about the Product Owner’s accountability to the Product Backlog within the Scrum framework and how the Product Backlog supports empiricism.

In this module, you will dive into how both the Product Goal and Product Backlog items must be transparent and how they are critical to creating and maintaining an effective Product Backlog.

The act of improving and further defining Product Backlogs items is called refinement. In this module, you will explore different Product Backlog refinement techniques like sizing and splitting items to help you manage your Product Backlog.

In this module, we build on the foundation of Product Backlog transparency to explore what it takes to make collaboration between the Scrum Team and its stakeholders truly effective. Stakeholder collaboration can be challenging for many reasons, such as conflicting priorities, unclear expectations, and limited engagement. Successful stakeholder collaboration occurs when there is effective communication between the Scrum Team and its stakeholders, allowing stakeholders to provide their input, expectations, and concerns. Regular and open interactions help foster a transparent environment and minimize surprises and interruptions. While ideal, this is easier said than done.

Artificial Intelligence (AI) is transforming the way people work, make decisions, and manage complex processes. In this module, we introduce areas in Product Backlog management where you can experiment with AI to complement the techniques we have already covered in the course. This includes examples, sample prompts, tips, and things to avoid. This “bonus” module is different from the previous ones in this course. To make the most of your learning, you will need to access and use an AI tool (there are many freely available that you can research and try), so that you can test the concepts we share.