AI & Machine Learning
Design Thinking & Product Development Using AI
Combine design thinking with AI to build better products.
2 daysIntermediate7 modules
About this course
Combine design thinking with AI to build better products. Over two days you will move through empathy, problem definition, ideation, prototyping, testing and delivery, learning to scope problems, align stakeholders and judge feasibility, viability and desirability.
What you'll learn
- Explain the foundational principles and history behind modern design frameworks
- Differentiate between sympathy, empathy, and compassion in user-centered design
- Analyze user contexts, behaviors, and needs using qualitative and quantitative methods
- Define clear, actionable problem statements and align stakeholders
- Generate, evaluate, and refine ideas using structured ideation techniques
- Assess the feasibility, viability, and desirability of proposed solutions
- Apply validation and testing methods to determine product value
- Identify what to build, what to ship, and when to iterate
- Understand trade-offs in agile and traditional delivery frameworks
- Recognize root causes of product and design challenges in modern applications
Curriculum
7 modules
- History of design frameworks and origin stories
- Core foundational principles across applications
- Modern context: challenges in conventional approaches
- Case study: cohorts and design challenge introduction
- Sympathy vs. Empathy vs. Compassion
- Understanding users, buyers, and consumers
- Importance of context and semantics
- Methods and tools: qualitative vs. quantitative research
- Scoping: avoiding “designing everything for everyone”
- Managing churn and unproductive debate
- Alignment: building agreement across teams
- Framing clear problem statements
- Concept generation: high-velocity thinking
- Avoiding attachment to ideas (“killing your darlings”)
- Directional vs. exploratory ideation
- Refinement: reducing variables and focusing solutions
- Feasibility: understanding what is possible
- Viability: designing what should be delivered
- Identifying the “golden path” (core interactions)
- Building prototypes at appropriate fidelity
- Desirability: user wants vs. actual needs
- Validation: identifying what creates value
- Invalidation: defining what is not valuable
- Best practices: bias prevention, research methods, sample sizing
- Deciding what to ship
- Production testing: determining “enough” vs. “too much”
- Agile considerations and competing frameworks (e.g., dual-track, BFFs)
- Modern context: root causes of product and system issues
Who it's for
Product managers, designers, innovation teams and entrepreneurs.
Before you start
- Basic understanding of product development or project workflows
- Familiarity with digital products or services (recommended but not required)
- No prior formal design training required
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