By the end of this course, you will be able to:

• Detect and analyze AI security threats. Identify vulnerabilities in machine learning models, recognize adversarial attack methods, and assess risks to AI-driven systems.
• Implement AI-specific intrusion detection and defense strategies. Use AI-powered security tools to safeguard data, models, and networks from evolving cyber threats.
• Develop forensic analysis skills for AI systems. Investigate AI-related security breaches, trace attack vectors, and apply forensic techniques to compromised models.
• Design and execute AI incident response plans. Build structured response strategies to mitigate security threats and reduce the impact of AI-driven cyber incidents.
• Enhance AI privacy and ethical security practices. Apply differential privacy, encryption, and ethical guidelines to secure AI applications while ensuring compliance.
• Prepare for future AI security challenges. Stay ahead of emerging risks, such as deepfake manipulation, AI-driven cyberattacks, and AI security automation trends.

If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals.

This intermediate-level course is designed for cybersecurity professionals, AI engineers, system administrators, and data scientists who need to secure machine learning systems and mitigate AI-driven threats. Individuals in threat analysis, incident response, and IT security roles will gain essential skills to detect vulnerabilities and build AI-specific defense strategies.

Technical managers, compliance professionals, and project leads overseeing AI security initiatives will also benefit from this course by gaining insights into governance, ethical AI considerations, and incident response frameworks. Whether you are directly securing AI systems or ensuring AI security compliance, this course equips you with the expertise to manage risks, strengthen security strategies, and build resilient AI-driven security solutions.

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We will collaborate with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience skill level, interests and participation. 

Introduction to AI in Security  

Explore foundational AI security, threat identification, and protective strategies through practical examples. 

• The Need for AI Security 
• Exploring AI Threat Landscape 
• Identify Threats and Implement Protections in AI Systems 
• Implement AI Security Best Practices 
• Top Ten Pitfalls to Avoid 
• Activity: Implementing Basic Security Measures 
• Benefits of Applying AI to Cybersecurity 

Playing Detective: Identifying AI Threats and Vulnerabilities 

Explore AI system vulnerabilities, different threat types, and data privacy concerns 

• Inherent threats and vulnerabilities of AI systems 
• Different types of AI threats  
• Common AI vulnerabilities  
• Case studies of major AI-based security breaches  

Building the AI Fortress: Defense Mechanisms 101 

Learn how to design and implement robust AI-driven defense systems. 

• Safeguard AI systems from security threats.  
• Deep Dive AI Security Measures 
• AI Defense Mechanisms 
• AI in intrusion detection and prevention systems  
• AI in risk assessment and vulnerability management 
• Activity: Design a basic AI-driven Intrusion Detection System  

AI Adversarial Attacks and Defenses  

Learn how to tackle adversarial threats to AI systems with effective defense strategies for security. 

• Adversarial attacks Deep Dive 
• Techniques to defend against adversarial attacks 
• Implementing defense measures against sample adversarial attacks 
• Activity: Defending Against Adversarial Attacks  

CSI Cyber: A Foray into AI Forensics  

Apply forensic techniques and analyzing AI security incidents. 

• How forensic techniques are applied in AI security.  
• Role of forensics in AI Security  
• Basics of AI Forensic Analysis  
• Case studies of forensic analysis in AI security incidents  
• AI in forensic data analysis  
• Activity: Conduct a simple forensic analysis on an AI system  

Crisis Averted: Crafting Your AI Incident Response Plan  

Develop and execute effective incident response plans for AI system breaches 

• How to respond to incidents in AI systems effectively.  
• Basics of Incident Response (IR) in AI systems  
• AI in IR: Automated and adaptive response  
• Designing an incident response plan for AI systems  

AI Privacy and Ethical Considerations  

Address privacy risks and ethical considerations in AI applications 

• Navigate privacy and ethics in AI to promote responsible technology use. 
• Privacy risks in AI/ML applications 
• Understanding differential privacy 
• Ethical considerations in AI Security 
• Hands-on Lab: Implementing differential privacy in a machine learning model 

What's Next? Preparing for Future AI Security Challenges  

Explore future AI security trends and prepare for emerging threats. 

• Get insights into the future trends of AI in cybersecurity. 
• Future threats: Deepfakes, autonomous weapons, etc.  
• AI in quantum computing security  
• AI-driven Security Orchestration, Automation, and Response (SOAR)  
• The role of AI in zero-trust architectures  

Bonus Chapters / Addendum 

• Next steps in Your AI Security Journey 
• Ethical AI Deeper Dive - Implementing Ethical AI in Everyday Business Practices 
• Everyday AI Security: Staying Safe and Smart with AI Tools 

Addendum / Resources 

• Course Site References & Additional Information 
• Glossary of Main Terms, Skills and Key Topics 
• Next Steps, Follow on Courses & SkillJourneys