Secure LLM Implementation Certificate

The Secure LLM Implementation Certificate is a seven-week, online program designed for leaders who are responsible for managing risk, ensuring compliance, and guiding teams through enterprise-scale adoption of large language models. As organizations increase their use of generative AI, new categories of security concerns have emerged, including data exposure, prompt injection, vendor vulnerabilities, and evolving regulatory requirements.

This program provides a clear and practical roadmap for secure implementation. Through interactive lectures, case studies, risk scenarios, and a final strategic capstone, participants gain the knowledge and confidence to oversee LLM deployment across complex business environments. The curriculum emphasizes leadership decision-making, governance design, and communication strategies that support safe and aligned AI use.

No technical or coding background is required.

Designed With You in Mind

Large language models introduce risks that are often distributed across security, legal, compliance, product, and IT functions without clear ownership. Misalignment between teams can lead to privacy incidents, regulatory failures, operational disruptions, and reputational harm.
This certificate was created for professionals who need a structured, accessible, and strategic approach to LLM security. Ideal participants include:

• Security and IT leaders expanding their scope into AI
• Executives and directors responsible for governance and risk oversight
• Legal, compliance, and privacy professionals responding to new regulatory expectations
• Product, data, and AI program owners delivering generative AI initiatives
• Anyone who must communicate AI risk and readiness to senior leadership

If you need to guide strategy, evaluate threats, prioritize resources, or design governance for generative AI systems, this program provides a clear foundation.

What You Will Learn

By the end of the Secure LLM Implementation Certificate, participants will be able to:

• Understand and assess LLM security risks
  • Identify vulnerabilities unique to LLMs, including data leakage, prompt injection, model drift, supply-chain exposure, and unsanctioned AI tools.
  • Evaluate risk across financial, operational, legal, and reputational dimensions.
• Build enterprise governance and oversight structures
  • Develop clear operating models, ownership roles, approval pathways, and vendor assurance processes that support secure and scalable AI deployment.
• Strengthen organizational readiness and coordination
  • Create policies, workflows, budgeting guidelines, and risk-scoring tools that align diverse stakeholders across the organization.
• Prepare for incident response and crisis communication
  • Detect and classify AI-specific incidents and communicate impact, remediation steps, and accountability to executives, boards, regulators, and customers.
• Develop a strategic roadmap for secure LLM adoption
  • Produce a practical organizational plan that guides secure implementation, long-term monitoring, and governance maturity.

Meet Your Instructor

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Jamie Wheeler is a technology executive with more than 25 years of experience at the intersection of engineering, analytics, and applied artificial intelligence. He has led major AI strategy, data governance, and secure systems initiatives across government and commercial sectors, holding leadership roles at C3 AI, Booz Allen Hamilton, Capgemini, and Alvarez and Marsal, where he supported senior government, DoD, Fortune 500, and G20 nation agency leadership. In addition to his industry work, Jamie serves as Coordinator and Lead Instructor for the Cyber Security Engineering master’s capstone at George Mason University and contributes to executive and professional education at Caltech, advising MBA students internationally on AI strategy, ethics, digital transformation, and emerging technology policy. Recognized for principled leadership and a strong grasp of how technology creates organizational value, he blends deep technical expertise with strategic vision and operational insight, helping executive teams drive innovation, manage risk, and translate complex ideas into measurable impact.

Why This Program Matters

Organizations are adopting generative AI faster than they are building the structures required to secure it. Large language models introduce new risks, including data exposure, unpredictable behavior, and reliance on external vendors, and these challenges cannot be managed with traditional security approaches alone. Many leaders are now accountable for AI-related decisions but lack the frameworks and training needed to guide teams, evaluate risks, and communicate clearly with executives and stakeholders.

This program provides a practical foundation for secure and responsible LLM adoption. Participants learn how to assess vulnerabilities, design governance and oversight models, coordinate cross-functional teams, and prepare their organizations for the ongoing demands of AI security and compliance. The result is stronger readiness, clearer decision-making, and greater confidence in deploying AI systems that support innovation while protecting the organization.