The Advanced Certified Scrum Product Owner (A-CSPO) course is designed for experienced Product Owners who want to deepen their expertise and advance their product ownership capabilities. This comprehensive training builds upon foundational Scrum knowledge to explore sophisticated techniques for product strategy, stakeholder management, customer empathy, and value delivery — with AI integrated as a working tool throughout the course rather than a separate topic. Participants will engage in hands-on exercises and real-world scenarios that combine timeless product ownership practices with AI-enabled approaches, developing advanced skills in managing complex product environments, working with multiple teams, and driving continuous product improvement through evidence-based decision making. The topics covered in the course include:

Product Owner Core Competencies

• Developing the mindset, behaviors, and actions that distinguish successful Product Owners
• Mastering advanced stakeholder interaction techniques for sustained engagement across multiple Sprints
• Using AI to translate the same prioritization decision into the language each stakeholder needs to hear
• Practicing facilitative listening techniques to improve communication and understanding
• Exploring alternative discussion formats beyond traditional open dialogue
• Implementing effective decision-making processes with diverse stakeholder groups
• Identifying development practices that enhance quality and reduce technical debt
• Recognizing and implementing approaches for scaling Scrum across multiple teams
• Managing and visualizing dependencies in complex product environments, with AI assistance to surface non-obvious risks

Advanced Goal Setting and Planning

• Examining real-world examples of how product strategy evolves in agile organizations
• Practicing multiple approaches to identify product purpose and define strategic direction
• Using AI as a sparring partner to stress-test product vision, Lean Canvas assumptions, and competitive positioning
• Creating collaborative product plans and forecasts with stakeholder input
• Mastering techniques for visualizing and communicating product strategy, ideas, features, and assumptions
• Generating scenario plans and reformatting roadmaps for different audiences using AI

Empathizing with Customers and Users

• Practicing advanced product discovery methods to uncover user needs and market opportunities
• Applying AI-assisted synthesis of user research, journey maps, and persona analysis to surface blind spots
• Recognizing how AI can both mitigate and amplify cognitive bias in customer understanding

Advanced Product Assumption Validation

• Identifying cognitive biases that can impact Product Owner effectiveness and business value delivery
• Evaluating Sprint Review effectiveness for inspection and adaptation based on Sprint Goals
• Comparing and contrasting different approaches to validating product assumptions
• Using AI to identify the riskiest assumptions in your product strategy and design experiments to test them
• Integrating assumption validation techniques seamlessly into the Scrum framework
• Developing testable hypotheses for target customer segments
• Creating comprehensive plans to test and validate product hypotheses
• Generating rapid AI-powered prototypes to make abstract assumptions concrete and testable

Product Backlog Management

• Applying multiple techniques for modeling and measuring product value (Kano, WSJF, RICE)
• Using AI to run sensitivity analyses on prioritization scores and flag overconfident assumptions
• Mastering advanced Product Backlog ordering techniques to support Product Goals
• Ensuring Product Backlog items are properly prepared and "ready" for upcoming Sprints
• Decomposing epics and generating edge-case acceptance criteria with AI assistance
• Integrating feedback from multiple sources to generate and refine Product Backlog items
• Experimenting with innovative approaches to improve Product Backlog refinement processes

Designing Your AI-Augmented PO Workflow

• Identifying your biggest real-world Product Owner bottleneck
• Designing a specific AI-assisted workflow to address it, with clear boundaries between what AI accelerates and what requires human judgment
• Recognizing what a Product Owner should never delegate to AI