Objectives of the training
This training course enables Product Owners to understand the fundamentals of artificial intelligence (AI), its use cases, limitations, and implications for product development. It gives them the keys to collaborating effectively with technical teams, framing AI projects, prioritizing features, and integrating AI into a user-centered agile approach.Targeted audience
Product OwnersPrerequisite
Knowledge of the Product Owner role and agile methods (Scrum, Kanban). No technical AI skills required.Trainers
Benefits for Participants
• Understand the key concepts of AI and machine learning.
• Identify opportunities for integrating AI into a product.
• Know how to frame an AI project as a PO (challenges, data, MVP).
• Collaborate effectively with data scientists and developers.
• Integrate AI into an agile, value-oriented roadmap.
Course architecture
Understanding the fundamentals of AI
Chapter 1: Introduction to artificial intelligence
• Definitions: AI, machine learning, deep learning
• Overview of technologies and algorithms
• Symbolic AI vs. statistical AI
Chapter 2: Use cases for AI in products
• Recommendation, classification, prediction, NLP, vision
• Examples in healthcare, finance, retail, HR
• Generative AI: uses and limitations
Workshop 1: Mapping AI use cases in your product
• Identifying AI opportunities in an existing backlog
• Prioritization based on value and feasibility
Framing an AI project as a PO
Chapter 3: The lifecycle of an AI project
• From data collection to production
• Specific features of an AI project vs. a traditional software project
• The concept of AI MVP
Chapter 4: The role of the PO in an AI project
• Writing AI user stories
• Defining business value and KPIs
• Collaborating with data scientists
Workshop 2: Writing AI user stories
• Examples of data-driven user stories
• Defining acceptance criteria for an AI model
Integrating AI into an agile approach
Chapter 5: Governance, ethics, and risks
• Algorithmic bias, explainability, Law 25
• User acceptability and transparency
• Best practices in AI governance
Chapter 6: Product and AI roadmap
• Integrating AI into an agile roadmap
• User testing and value validation
• Continuous measurement of model performance
Workshop 3: Building an AI roadmap
• Developing a product roadmap that integrates AI building blocks
• Identifying dependencies and risks
Pedagogical details
Type of training
Private or personalized training
Do you have several employees interested in the same training course? Whether in person at your offices or remotely in virtual mode, we offer private training courses tailored to your team's needs. Group rates are available. Contact us for more details or request a quote online.
Request a quotePrivate or personalized training
Do you have several employees interested in the same training course? Whether in person at your offices or remotely in virtual mode, we offer private training courses tailored to your team's needs. Group rates are available. Contact us for more details or request a quote online.
Request a quote