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AI Governance, Compliance, and Security for Enterprise Leaders

 14 Hours
This instructor-led, live training in Botswana (online or onsite) is aimed at intermediate-level enterprise leaders who wish to understand how to govern and secure AI systems responsibly and in compliance with emerging global frameworks such as the EU AI Act, GDPR, ISO/IEC 42001, and the U.S. Executive Order on AI.By the end of this training, participants will be able to:
  • Understand the legal, ethical, and regulatory risks of using AI across departments.
  • Interpret and apply major AI governance frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001).
  • Establish security, auditing, and oversight policies for AI deployment in the enterprise.
  • Develop procurement and usage guidelines for third-party and in-house AI systems.
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Building Secure and Responsible LLM Applications

 14 Hours
This instructor-led, live training in Botswana (online or onsite) is aimed at intermediate-level to advanced-level AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.By the end of this training, participants will be able to:
  • Understand the core vulnerabilities of LLM-based systems.
  • Apply secure design principles to LLM app architecture.
  • Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
  • Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.
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Securing AI Models: Threats, Attacks, and Defenses

 14 Hours
This instructor-led, live training in Botswana (online or onsite) is aimed at intermediate-level machine learning and cybersecurity professionals who wish to understand and mitigate emerging threats against AI models, using both conceptual frameworks and hands-on defenses like robust training and differential privacy.By the end of this training, participants will be able to:
  • Identify and classify AI-specific threats such as adversarial attacks, inversion, and poisoning.
  • Use tools like the Adversarial Robustness Toolbox (ART) to simulate attacks and test models.
  • Apply practical defenses including adversarial training, noise injection, and privacy-preserving techniques.
  • Design threat-aware model evaluation strategies in production environments.
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Introduction to AI Security and Risk Management

 14 Hours
This instructor-led, live training in Botswana (online or onsite) is aimed at beginner-level IT security, risk, and compliance professionals who wish to understand foundational AI security concepts, threat vectors, and global frameworks such as NIST AI RMF and ISO/IEC 42001.By the end of this training, participants will be able to:
  • Understand the unique security risks introduced by AI systems.
  • Identify threat vectors such as adversarial attacks, data poisoning, and model inversion.
  • Apply foundational governance models like the NIST AI Risk Management Framework.
  • Align AI use with emerging standards, compliance guidelines, and ethical principles.
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