Privacy-Preserving Machine Learning Training Course

The AAISM framework provides advanced tools for evaluating, directing, and overseeing security risks within artificial intelligence ecosystems.

Delivered as a live, instructor-led program—available either online or on-site—this course is designed for senior professionals seeking to establish robust security controls and governance standards for enterprise AI environments.

By the end of this program, participants will be equipped to:

• Assess AI security risks utilizing established industry methodologies.
• Develop governance structures that ensure responsible AI deployment.
• Align AI security strategies with organizational objectives and regulatory requirements.
• Strengthen resilience and accountability in AI-driven operational processes.

Course Delivery Method

• Expert-led discussions featuring in-depth analysis.
• Hands-on workshops and competency-based assessments.
• Practical applications based on real-world AI governance cases.

Customization Possibilities

• To tailor the training to your specific organizational AI strategy, please reach out to discuss course customization.

This instructor-led live training in Thailand (online or onsite) is designed for intermediate-level enterprise leaders seeking to master the responsible governance and security of AI systems. The curriculum ensures alignment with emerging global frameworks, including the EU AI Act, GDPR, ISO/IEC 42001, and the U.S. Executive Order on AI.

By the end of the session, participants will be capable of:

• Identifying and managing legal, ethical, and regulatory risks in departmental AI applications.
• Applying major AI governance frameworks, including the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
• Defining security, auditing, and oversight protocols for enterprise AI deployment.
• Establishing procurement and usage standards for third-party and in-house AI solutions.

The integration of Artificial Intelligence (AI) introduces novel dimensions of operational risk, governance complexities, and expanded cybersecurity exposure for government agencies and departments.

Designed for public sector IT and risk professionals with limited prior AI experience, this instructor-led, live training (available online or onsite) guides participants on how to effectively evaluate, monitor, and secure AI systems within a government or regulatory environment.

Upon completion, participants will be equipped to:

• Interpret core risk concepts specific to AI systems, such as bias, unpredictability, and model drift.
• Implement AI-specific governance and auditing frameworks, including the NIST AI RMF and ISO/IEC 42001.
• Identify cybersecurity threats that target AI models and data pipelines.
• Develop cross-departmental risk management strategies and align policies for AI deployment.

Course Format

• Engaging lectures and discussions focused on public sector use cases.
• Hands-on exercises involving AI governance frameworks and policy mapping.
• Scenario-based activities for threat modeling and risk assessment.

Customization Options

• For tailored training solutions, please contact us to discuss your specific requirements.

This course provides a practical introduction to securing modern AI-powered applications, APIs, copilots, and autonomous agents. Participants learn how AI security differs 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 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 Thailand (online or onsite) is tailored for IT professionals from beginner to intermediate levels who aim to understand and implement AI TRiSM in their respective organizations.

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

• Comprehend the core principles and significance of managing trust, risk, and security in AI.
• Recognize and reduce risks inherent in AI systems.
• Apply established security best practices to AI deployments.
• Navigate regulatory compliance and ethical implications surrounding AI.
• Formulate strategies for robust AI governance and operational management.

This live, instructor-led training in Thailand (online or onsite) is designed for intermediate to advanced AI developers, architects, and product managers aiming to identify and mitigate risks associated with LLM-powered applications. It addresses threats such as prompt injection, data leakage, and unfiltered output, while guiding the integration of security controls like input validation, human-in-the-loop oversight, and output guardrails.

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

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Utilize 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 with inherent security. Participants learn to protect chatbots, copilots, RAG pipelines, and AI agents from AI-specific threats, including prompt injection, data poisoning, tool abuse, secret leakage, and insecure model outputs. The course covers secure prompt design, RAG security, least-privilege access, guardrails, and red-team testing, enabling developers to create AI features that are secure, reliable, and resilient in production environments.

This instructor-led, live training in Thailand (online or onsite) targets intermediate AI and cybersecurity professionals aiming to master the security vulnerabilities associated with AI models and systems, especially within highly regulated sectors like finance, data governance, and consulting.

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

• Recognize adversarial attack vectors against AI systems and implement corresponding defense mechanisms.
• Utilize model hardening techniques to protect machine learning pipelines.
• Maintain data security and integrity within machine learning frameworks.
• Comply with regulatory requirements pertaining to AI security.

This live, instructor-led training in Thailand (delivered online or on-site) targets security engineers and compliance officers seeking to fortify EXO deployments, manage model access, and govern on-premise AI workloads.

This live, instructor-led training in Thailand (available online or on-site) is tailored for entry-level professionals in IT security, risk, and compliance. It aims to foster a deep understanding of core AI security concepts, threat vectors, and global standards like the NIST AI RMF and ISO/IEC 42001.

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

• Understand the unique security challenges posed by AI systems.
• Identify specific threats, such as adversarial attacks, data poisoning, and model inversion.
• Apply core governance models, including the NIST AI Risk Management Framework.
• Align AI deployments with emerging standards, regulatory guidelines, and ethical norms.

This live, instructor-led course in Thailand (online or onsite) is designed for security and ML engineers who need to identify, test, and defend ML models and LLM-powered applications against emerging threats.

Aligned with the latest OWASP GenAI Security Project guidance, this training enables participants to identify, assess, and mitigate AI-specific threats through practical exercises and real-world scenario analysis.

This instructor-led live training, conducted in Thailand (either online or onsite), is designed for senior security professionals and ML experts who aim to simulate attacks on AI systems, detect vulnerabilities, and improve the robustness of deployed AI models.

By the conclusion of this training, participants will be capable of:

• Replicating real-world threats to machine learning models.
• Producing adversarial examples to challenge model robustness.
• Analyzing the attack surface of AI APIs and pipelines.
• Crafting red teaming strategies for AI deployment contexts.

This instructor-led live training, conducted in Thailand (either online or on-site), targets intermediate-level engineers and security specialists looking to secure edge-deployed AI models against threats such as tampering, data exfiltration, adversarial inputs, and physical breaches.

By the end of the program, attendees will possess the ability to:

• Detect and evaluate security risks associated with edge AI deployments.
• Implement tamper-resistant features and encrypted inference protocols.
• Fortify models at the edge and safeguard data pipelines.
• Deploy threat mitigation strategies appropriate for embedded and constrained systems.

Delivered by an instructor in Thailand (online or onsite), this session targets mid-level ML and cybersecurity experts looking to grasp and counter new risks to AI models, combining conceptual understanding with practical defenses such as robust training and differential privacy.

Upon completion, participants will be equipped to:

• Recognize and categorize AI-specific threats like adversarial attacks, inversion, and poisoning.
• Utilize tools like the Adversarial Robustness Toolbox (ART) to simulate attacks and evaluate models.
• Implement practical countermeasures such as adversarial training, noise injection, and privacy-preserving methods.
• Develop threat-aware model assessment strategies for production environments.