Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Secure and Ethical AI
- Overview of AI security and ethics.
- Common threats and vulnerabilities within AI systems.
- The regulatory landscape and compliance frameworks.
Security Threats in AI Agents
- Data poisoning and model manipulation.
- Adversarial attacks on AI models.
- Strategies for mitigating AI security threats.
Building Robust and Secure AI Models
- The secure AI development lifecycle.
- Defensive machine learning techniques.
- AI model validation and testing processes.
Ethical AI Development and Fairness
- Detecting and mitigating bias in AI models.
- Explainability and transparency in AI decision-making.
- Ensuring responsible AI deployment.
AI Governance, Compliance, and Risk Management
- Compliance with GDPR, CCPA, and the AI Act.
- Risk management frameworks for AI security.
- Auditing AI models for security and ethical concerns.
Secure AI Deployment Best Practices
- Deploying AI agents with security prioritised.
- Monitoring AI models for anomalies and vulnerabilities.
- Responding to and mitigating AI security incidents.
Case Studies and Real-World Applications
- Case studies on AI security breaches and key lessons.
- Implementing secure AI agents in real-world scenarios.
- Best practices for future-proofing AI security.
Summary and Next Steps
Requirements
- A solid understanding of AI and machine learning concepts.
- Practical experience with Python and relevant AI frameworks.
- Foundational knowledge of cybersecurity principles.
Target Audience
- AI developers.
- Security specialists.
- Compliance officers.
14 Hours
