Advanced Skill Certificate in AI Security for Critical Infrastructure
-- viewing nowAI Security for Critical Infrastructure is a specialized field that focuses on protecting Artificial Intelligence systems from cyber threats. This Advanced Skill Certificate program is designed for information security professionals and IT experts who want to enhance their knowledge in AI security.
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About this course
Learn how to identify and mitigate risks associated with AI-powered systems, including machine learning and deep learning models. Discover how to implement secure AI development practices, ensure data privacy, and protect against adversarial attacks.
Develop the skills needed to safeguard critical infrastructure, including power grids, financial systems, and healthcare networks. Take the first step towards a career in AI security and explore this program further to learn more.
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Course details
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Artificial Intelligence (AI) Fundamentals: This unit covers the basics of AI, including machine learning, deep learning, and natural language processing, which are essential for understanding AI security in critical infrastructure. •
Cybersecurity Frameworks and Standards: This unit introduces students to various cybersecurity frameworks and standards, such as NIST Cybersecurity Framework, ISO 27001, and PCI-DSS, which are crucial for securing AI systems in critical infrastructure. •
Threat Intelligence and Vulnerability Assessment: This unit teaches students to identify and assess threats to AI systems in critical infrastructure, including vulnerabilities and potential attack vectors, and how to mitigate them. •
AI Security Architecture: This unit covers the design and implementation of secure AI architectures, including data storage, processing, and transmission, to prevent unauthorized access and data breaches in critical infrastructure. •
Machine Learning Security: This unit focuses on the security of machine learning models, including model vulnerability assessment, model explainability, and model security testing, to prevent adversarial attacks in critical infrastructure. •
Cloud Security for AI: This unit introduces students to cloud security measures for AI systems, including cloud storage, cloud processing, and cloud networking, to ensure secure deployment and management of AI in critical infrastructure. •
Human Factors in AI Security: This unit explores the importance of human factors in AI security, including user behavior, social engineering, and organizational security, to prevent insider threats in critical infrastructure. •
AI-Powered Threat Detection and Response: This unit teaches students to use AI-powered tools for threat detection and response, including anomaly detection, incident response, and threat intelligence, to quickly respond to security incidents in critical infrastructure. •
Secure Data Analytics for AI: This unit covers the principles of secure data analytics for AI, including data quality, data governance, and data protection, to ensure that AI systems in critical infrastructure provide accurate and trustworthy insights. •
AI Security Governance and Compliance: This unit introduces students to AI security governance and compliance, including regulatory requirements, industry standards, and organizational policies, to ensure that AI systems in critical infrastructure meet security and regulatory standards.
Artificial Intelligence (AI) Fundamentals: This unit covers the basics of AI, including machine learning, deep learning, and natural language processing, which are essential for understanding AI security in critical infrastructure. •
Cybersecurity Frameworks and Standards: This unit introduces students to various cybersecurity frameworks and standards, such as NIST Cybersecurity Framework, ISO 27001, and PCI-DSS, which are crucial for securing AI systems in critical infrastructure. •
Threat Intelligence and Vulnerability Assessment: This unit teaches students to identify and assess threats to AI systems in critical infrastructure, including vulnerabilities and potential attack vectors, and how to mitigate them. •
AI Security Architecture: This unit covers the design and implementation of secure AI architectures, including data storage, processing, and transmission, to prevent unauthorized access and data breaches in critical infrastructure. •
Machine Learning Security: This unit focuses on the security of machine learning models, including model vulnerability assessment, model explainability, and model security testing, to prevent adversarial attacks in critical infrastructure. •
Cloud Security for AI: This unit introduces students to cloud security measures for AI systems, including cloud storage, cloud processing, and cloud networking, to ensure secure deployment and management of AI in critical infrastructure. •
Human Factors in AI Security: This unit explores the importance of human factors in AI security, including user behavior, social engineering, and organizational security, to prevent insider threats in critical infrastructure. •
AI-Powered Threat Detection and Response: This unit teaches students to use AI-powered tools for threat detection and response, including anomaly detection, incident response, and threat intelligence, to quickly respond to security incidents in critical infrastructure. •
Secure Data Analytics for AI: This unit covers the principles of secure data analytics for AI, including data quality, data governance, and data protection, to ensure that AI systems in critical infrastructure provide accurate and trustworthy insights. •
AI Security Governance and Compliance: This unit introduces students to AI security governance and compliance, including regulatory requirements, industry standards, and organizational policies, to ensure that AI systems in critical infrastructure meet security and regulatory standards.
Career path
| **Role** | **Description** |
|---|---|
| Cybersecurity Analyst | Conduct risk assessments, implement security measures, and respond to security incidents to protect critical infrastructure from cyber threats. |
| Information Security Analyst | Develop and implement information security policies, procedures, and controls to protect sensitive data and systems. |
| Penetration Tester | Simulate cyber attacks on computer systems to test their defenses and identify vulnerabilities. |
| Incident Responder | Respond to and manage security incidents, including containing and eradicating malware, and restoring systems to normal operation. |
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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ADVANCED SKILL CERTIFICATE IN AI SECURITY FOR CRITICAL INFRASTRUCTURE
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who has completed a programme at
London School of Planning and Management (LSPM)
Awarded on
05 May 2025
Blockchain Id: s-1-a-2-m-3-p-4-l-5-e
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