Security and Privacy in TinyML Applications Training Course

This instructor-led, live training in the UAE (online or onsite) targets intermediate-level enterprise leaders seeking to understand how to responsibly govern and secure AI systems in compliance with emerging global frameworks such as the EU AI Act, GDPR, ISO/IEC 42001, and the U.S. Executive Order on AI.

Upon completing this training, participants will be able to:

• Grasp the legal, ethical, and regulatory risks associated with AI usage across departments.
• Interpret and apply key AI governance frameworks such as the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
• Establish robust security, auditing, and oversight policies for AI deployment within the enterprise.
• Develop procurement and usage guidelines for both third-party and in-house AI systems.

This course offers a practical introduction to securing modern AI-powered applications, APIs, copilots, and autonomous agents. Participants will learn how AI security diverges from traditional web security, explore common AI-specific threats such as prompt injection, RAG poisoning, and agent abuse, and understand how to protect AI systems using layered defenses including WAFs, AI gateways, API security, and guardrails. Through hands-on labs and real-world examples, students will gain the skills to identify AI attack patterns, secure LLM-based applications, and deploy effective runtime defenses for production environments.

This instructor-led, live training in the UAE (online or onsite) is designed for beginner to intermediate-level IT professionals aiming to understand and implement AI TRiSM within their organizations.

Upon completion of this training, participants will be capable of:

• Grasping the core concepts and significance of managing trust, risk, and security in AI.
• Identifying and mitigating potential risks associated with AI implementations.
• Applying security best practices specifically tailored for AI technologies.
• Understanding regulatory compliance requirements and ethical considerations in AI.
• Formulating strategies for effective AI governance and management.

This instructor-led, live training in the UAE (online or onsite) targets intermediate to advanced AI developers, architects, and product managers seeking to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while implementing 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.

This course teaches software developers how to build AI-powered applications securely by design. Participants learn how to protect chatbots, copilots, RAG pipelines, and AI agents against AI-specific threats such as prompt injection, data poisoning, tool abuse, secret leakage, and insecure model output. The course covers secure prompt design, RAG security, least-privilege access, guardrails, and red-team testing, helping developers build AI features that are secure, reliable, and resilient in real-world environments.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level AI and cybersecurity professionals who wish to understand and address the security vulnerabilities specific to AI models and systems, particularly in highly regulated industries such as finance, data governance, and consulting.

By the end of this training, participants will be able to:

• Understand the types of adversarial attacks targeting AI systems and methods to defend against them.
• Implement model hardening techniques to secure machine learning pipelines.
• Ensure data security and integrity in machine learning models.
• Navigate regulatory compliance requirements related to AI security.

This instructor-led live training in the UAE (online or onsite) is targeted at security engineers and compliance officers who wish to harden EXO deployments, control model access, and govern AI workloads running entirely on-premise.

This instructor-led, live training in the UAE (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.

This instructor-led, live training in the UAE (online or onsite) is aimed at security and ML engineers who need to identify, test, and defend against attacks on ML models and LLM-powered applications.

Guided by the latest OWASP GenAI Security Project recommendations, participants will learn to identify, evaluate, and mitigate AI-specific threats through interactive exercises and real-world scenarios.

This instructor-led live training in the UAE (online or onsite) is designed for advanced professionals seeking to implement and assess techniques like federated learning, secure multiparty computation, homomorphic encryption, and differential privacy in real-world machine learning contexts.

By the conclusion of this training, participants will be able to:

• Understand and compare essential privacy-preserving techniques in ML.
• Implement federated learning systems using open-source frameworks.
• Apply differential privacy for secure data sharing and model training.
• Use encryption and secure computation techniques to protect model inputs and outputs.

This instructor-led, live training in the UAE (online or onsite) targets advanced-level security professionals and ML specialists who aim to simulate attacks on AI systems, uncover vulnerabilities, and enhance the robustness of deployed AI models.

Upon completing this training, participants will be equipped to:

• Simulate real-world threats targeting machine learning models.
• Generate adversarial examples to evaluate model robustness.
• Assess the attack surface of AI APIs and pipelines.
• Develop red teaming strategies for AI deployment environments.

This instructor-led, live training in the UAE (online or onsite) is designed for intermediate-level engineers and security professionals aiming to secure edge-deployed AI models against threats including tampering, data leakage, adversarial inputs, and physical attacks.

Upon completion of this training, participants will be able to:

• Identify and evaluate security risks associated with edge AI deployments.
• Implement tamper-resistant and encrypted inference techniques.
• Harden models deployed at the edge and secure data pipelines.
• Deploy threat mitigation strategies tailored for embedded and constrained systems.