Model Selection and Deployment Planning

This unit guides learners through evaluating foundation models, assessing data and technology needs, and translating ethical, compliance, and business requirements into a technical vision and deployment plan. Students will conduct gap and skills analyses, prioritize use cases, and create resource- and budget-aware recommendations that prepare teams for implementation and operationalization.

Learning Objectives

• Analyze organizational goals, use-case value, and preliminary technology gaps to prioritize a winning generative AI use case supported by evidence from case studies and gap-analysis outputs
• Evaluate foundation model options and data-resource requirements against compliance, explainability, and bias-mitigation criteria to recommend an accountable model selection
• Design a coherent technical vision and deployment plan that specifies data architecture, technology stack, fine-tuning/RAG/agent approaches, and a resource allocation and budget estimate for implementation
• Conduct a company-wide data skills survey and audit and produce executive-level recommendations for data literacy, governance, and KPIs that enable sustainable AI adoption