This capstone unit focuses on taking an AI/data strategy from plan to production by addressing deployment, cost, staffing, vendor management, monitoring, risk mitigation, and ethics. Students synthesize Agile/DevOps practices, infrastructure and compute assessments, stakeholder communication, and maintenance strategies to produce a practical, scalable implementation roadmap.
Learning Objectives
- Analyze infrastructure, compute, and total cost of ownership for foundation models and retrieval-augmented solutions and produce a clear cost-estimate report with ROI and scalability implications
- Evaluate vendor relationships, contractual terms, and vendor-management options and recommend a vendor management plan that includes SLAs, KPIs, and escalation procedures
- Develop a comprehensive deployment and monitoring plan that applies Agile and DevOps principles, outlines maintenance and contingency procedures, and addresses model-specific monitoring and security needs
- Design and present a stakeholder-facing project pitch and hiring plan that justifies resource allocation, assigns roles and responsibilities, and integrates ethical, legal, and advanced risk-mitigation strategies
Curriculum
- 1 Section
- 22 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 4 — Operationalizing Data & AI Strategy22
- 1.1Deploying AI with Agile and DevOps Principles20 mins
- 1.2Identifying Your Best-Fit Use Cases20 mins
- 1.3Assessing Infrastructure and Compute Costs for Foundation Models20 mins
- 1.4How to Pitch Your Project to High-Influence Stakeholders20 mins
- 1.5Formulating Hiring Recommendations20 mins
- 1.6Risk Management and Contingencies20 mins
- 1.7Notes20 mins
- 1.8Note20 mins
- 1.9Common Pitfalls and Best Practices20 mins
- 1.10Additional Considerations for Generative AI Use Cases20 mins
- 1.11Assessing Vendor Relationships and Recommending a Plan for Vendor Management20 mins
- 1.12Monitoring and Management Mechanisms20 mins
- 1.13Recommended Reading20 mins
- 1.14Considerations When Building with Foundation Models20 mins
- 1.15Addressing Ethical and Societal Implications of Foundation Models20 mins
- 1.16Advanced Project Management for Data Strategies20 mins
- 1.17Considerations When Deploying Retrieval-Augmented Generation20 mins
- 1.18Monitoring and Maintenance Challenges When Building with Foundation Models20 mins
- 1.19Wrapping Up Your Strategic Plan20 mins
- 1.20Advanced Risk Mitigation and Management in Data Projects20 mins
- 1.21Tools, Technologies, and Resources for Streamlined Implementation20 mins
- 1.22This Is Just the Beginning20 mins
Instructor
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