This unit teaches learners to translate organizational needs into well-scoped AI use cases, evaluate the ecosystem of partners and global R&D factors, and assess data, privacy, and model-selection tradeoffs. It builds on foundational AI concepts introduced earlier and prepares students to design implementation plans and governance in the final unit.
Learning Objectives
- Analyze organizational processes and strategic goals to define, prioritize, and document high-value AI use cases using cost-benefit and risk criteria
- Evaluate internal and external partnership models, including global R&D considerations, and recommend governance structures and stakeholder roles to support selected use cases
- Demonstrate methods for assessing data availability, quality, privacy, and democratization constraints, and propose mitigation strategies that align with legal and ethical requirements
- Apply model-selection and deployment criteria — including limitations related to black swan events and operational controllability — to recommend an appropriate AI model and rollout approach for a specified industry use case
Curriculum
- 1 Section
- 13 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 3 — Identifying and Scoping AI Use Cases13
- 1.1Answering the Right Questions20 mins
- 1.2Learning from the Future20 mins
- 1.3Knowing Which Buttons to Push20 mins
- 1.4AI R&D Will Span the Globe20 mins
- 1.5AI Cannot Anticipate Black Swan Events20 mins
- 1.6Defining Use Cases20 mins
- 1.7The Critical Role of Internal and External Partnerships20 mins
- 1.8Examining the Use Cases20 mins
- 1.9Examining Key Industries20 mins
- 1.10Examining the Use Cases20 mins
- 1.11The Data Privacy Iceberg Will Emerge20 mins
- 1.12AI Might Be Democratized, but Data Is Not20 mins
- 1.13Choosing a Model20 mins
Instructor
Leave a Reply