Overview
AI Product Development guides participants through transforming a validated user problem into a useful, trustworthy and commercially viable AI-powered product. The course covers opportunity discovery, use-case prioritisation, product requirements, data and model options, user experience, prototyping, testing and launch planning. Participants also examine product metrics, human oversight, risk management, governance and continuous improvement. Each learner or team develops an AI product concept, prototype plan and implementation roadmap.
Course Highlights
AI opportunity discovery
Use-case prioritisation
AI product requirements and metrics
Data, model and API selection
Prototyping and user testing
Launch, governance and improvement
Modules & Curriculum
AI Opportunity Discovery and User Problems
Use-Case Prioritisation, Value, Feasibility and Risk
AI Product Requirements, Metrics and User Experience
Data, Model and API Selection
Prototype and Proof-of-Concept Development
AI Product Testing and User Validation
Launch, Monitoring, Governance and Improvement
Learning Outcomes
- Identify valuable user problems and suitable AI product opportunities.
- Assess AI use cases based on value, feasibility, risk and strategic fit.
- Develop clear product requirements, success metrics and acceptance criteria.
- Compare data, model, API and technology options for an AI product.
- Design user experiences that communicate AI capabilities and limitations.
- Plan and evaluate prototypes and proof-of-concept solutions.
- Define testing, human-oversight and risk-management requirements.
- Prepare a responsible launch, monitoring and continuous-improvement plan.
- Present an evidence-based AI product roadmap.
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