Build the Skills to Design, Deliver, and Manage AI-Driven Products
Through a comprehensive exploration of foundational principles, practical frameworks, and hands-on activities, learners will gain expertise in developing and managing AI-driven products that align with business goals and deliver measurable outcomes.
What you’ll learn
- Understand AI Product Management and its differences from traditional Product Management..
- Apply the Product Operating Model to organize teams and achieve outcomes..
- Develop AI product strategies that align with business goals..
- Execute discovery processes to validate problems and identify effective solutions..
- Deliver and manage AI products using CI/CD principles and ML Ops frameworks..
- Build leadership and expertise in AI Product Management to grow their careers..
Course Content
- Course Introduction –> 2 lectures • 15min.
- Module 1 | Introduction to AI Product Management –> 1 lecture • 10min.
- Module 2 | Adopting the Product Operating Model –> 1 lecture • 13min.
- Module 3 | Foundations of AI Products –> 1 lecture • 15min.
- Module 4 | AI Product Strategy –> 1 lecture • 17min.
- Module 5 | AI Product Discovery –> 1 lecture • 16min.
- Module 6 | AI Product Delivery & ML Ops –> 1 lecture • 12min.
- Module 7 | Growing Your Career in AI Product Management –> 1 lecture • 9min.
- Module 8 | Key Takeaways & Course Project –> 1 lecture • 9min.
Requirements
Through a comprehensive exploration of foundational principles, practical frameworks, and hands-on activities, learners will gain expertise in developing and managing AI-driven products that align with business goals and deliver measurable outcomes.
Module 1: Introduction to AI Product Management
Topics Covered:
- What is AI Product Management?
- How AI Product Management differs from traditional Product Management.
- Key responsibilities, skills, and competencies of AI Product Managers.
Key Takeaways:
- Understand the framework for creating model-driven products.
- Identify the unique value AI Product Managers bring to organizations.
Module 2: Adopting the Product Operating Model
Topics Covered:
- Overview of the Product Operating Model.
- Roles of Product Managers, Data Scientists, Tech Leads, and Product Leadership.
- How to organize teams around value, usability, feasibility, and viability.
Key Takeaways:
- Learn how to deliver measurable outcomes using the Product Operating Model.
Module 3: Foundations of AI Products
Topics Covered:
- Overview of AI branches (e.g., machine learning, NLP, vision, generative AI).
- How AI algorithms and workflows function.
- Managing AI products effectively.
Key Takeaways:
- Build a foundational understanding of AI concepts and applications.
Module 4: AI Product Strategy
Topics Covered:
- Principles of AI Product Strategy: Focus, Data-Driven Insights, Transparency, and Placing Bets.
- How to align AI goals with business objectives.
Key Takeaways:
- Develop strategic thinking to identify and prioritize high-impact problems.
Module 5: AI Product Discovery
Topics Covered:
- Validating problems, assessing risks, and rapid experimentation.
- Principles of discovery: minimize waste, assess risks, and validate solutions.
Key Takeaways:
- Understand how product discovery ensures solutions are valuable, usable, feasible, and viable.
Module 6: AI Product Delivery & ML Ops
Topics Covered:
- CI/CD and iterative development in AI product delivery.
- ML Ops lifecycle: Development, Deployment, Monitoring, and Retraining.
Key Takeaways:
- Learn how to ensure reliability, scalability, and adaptability of AI solutions.
Module 7: Growing Your Career in AI Product Management
Topics Covered:
- Building expertise as an AI Product Manager.
- Leadership in AI Product Management and ethical AI practices.
- Strategies for continuous learning and staying updated.
Key Takeaways:
- Develop a roadmap for career advancement in AI Product Management.
Module 8: Key Takeaways & Course Project
Topics Covered:
- Summary of course modules and frameworks.
- Real-world application of the AI Product Management Framework.
Key Takeaways:
- Synthesize key learnings into a portfolio-ready course project.
Course Project: Design a recommendation system for an e-commerce platform, focusing on strategy, discovery, and delivery phases. Create a final presentation summarizing your findings, solutions, and outcomes.
Learning Outcomes
By the end of this course, participants will:
- Understand the unique aspects of AI Product Management and its differences from traditional Product Management.
- Apply the Product Operating Model to organize teams and achieve outcomes.
- Develop AI product strategies that align with business goals.
- Execute discovery processes to validate problems and identify effective solutions.
- Deliver and manage AI products using CI/CD principles and ML Ops frameworks.
- Build leadership and expertise in AI Product Management to grow their careers.
Course Logistics
• Duration: 8 Modules
• Delivery Mode: Online, self-paced
• Certificate of Completion: Awarded upon successful completion of all activities and the final project.