Introduction
AI products require thoughtful design, rigorous evaluation, and user-centric decision-making. This course teaches the unique principles of managing AI products from ideation to deployment. Participants will learn how to define AI product strategy, collaborate with technical teams, and measure product performance. Emphasis is placed on ethical considerations and responsible design. By the end, learners will be ready to lead AI product initiatives.
Course Objectives
- Develop strategic AI product roadmaps
- Translate business needs into AI features
- Collaborate effectively with data/engineering teams
- Evaluate AI product success metrics
- Apply responsible AI guidelines
Target Audience
- Product managers
- Startup founders
- Project leads
- Business strategists
- Students entering product roles
Course Outline
- 5 Sections
- 0 Lessons
- 5 Days
Expand all sectionsCollapse all sections
- Day 1: AI Product Landscape• What makes AI products unique
• Product vs. model success
• AI opportunity identification
• Market analyses
• Case studies0 - Day 2: Problem-Framing & Requirements• User needs discovery
• Data and labeling requirements
• Feasibility assessment
• Success metrics
• Hands-on: Write PRDs0 - Day 3: Working With Technical Teams• ML lifecycle
• Cross-functional collaboration
• Experimentation workflows
• Managing uncertainty
• Role-mapping exercises0 - Day 4: Launching AI Products• Deployment strategies
• UX considerations for AI
• Monitoring and iteration
• Change management
• Hands-on: Launch plan0 - Day 5: Responsible AI Product Design• Fairness and transparency
• Human-in-the-loop systems
• Failure case analysis
• AI governance
• Capstone product strategy0
Instructor
Lessons:
