Generative AI Cybersecurity & Privacy for Leaders Specialization course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Foundations of Generative AI for Cybersecurity Leaders
Estimated time: 12 hours
- Introduction to generative AI concepts for security leaders
- Understanding Large Language Models (LLMs) and their capabilities
- Limitations of LLMs in cybersecurity contexts
- Real-world examples of AI in cyber offense and defense
Module 2: Generative AI in Cyber Threats and Defense
Estimated time: 16 hours
- How attackers use generative AI for phishing and social engineering
- AI-powered malware creation and evasion techniques
- AI-driven defense mechanisms: threat analysis and detection
- Role of AI in Security Operations Centers (SOCs)
Module 3: Risk Management, Governance, and Compliance
Estimated time: 10 hours
- Regulatory and legal considerations for AI in cybersecurity
- Ethical implications of AI deployment
- Managing risks: data leakage, hallucinations, adversarial attacks
- Building governance frameworks for compliant AI adoption
Module 4: Leading AI Adoption in Cybersecurity
Estimated time: 12 hours
- Leading cross-functional teams in AI initiatives
- Managing organizational change with AI integration
- Workforce readiness and upskilling for AI-driven operations
- Aligning AI security with business and risk objectives
Module 5: Capstone Project: Generative AI Cybersecurity Strategy
Estimated time: 20 hours
- Design a comprehensive AI cybersecurity strategy for a simulated organization
- Define governance, priorities, and risk mitigation measures
- Develop a leadership-ready roadmap with success metrics
Prerequisites
- Basic understanding of cybersecurity principles
- Familiarity with organizational risk management concepts
- Experience in leadership or decision-making role preferred
What You'll Be Able to Do After
- Understand how generative AI impacts cyber threats and defenses
- Evaluate risks associated with AI adoption in security
- Develop governance and compliance strategies for AI use
- Create a strategic plan for AI integration in cybersecurity programs
- Lead organizational AI adoption with a focus on resilience and ethics