Practitioner's Playbook for RSAIFTM
A hands-on program on securing AI systems, covering ethical AI governance, threat identification, and security practices across the AI lifecycle.
Practical AI security, from design to deployment
- Available In:
English - Duration:
8 hours - Format:
Practical AI security strategies and tools for ethical governance and robust security
Prerequisites
- Familiarity with AI systems and basic security principles
The Practitioner’s Playbook for RSAIF™ self-paced course includes:
1. 8 hours of on-demand videos, an e-book, and podcasts.
2. Modular quizzes to help learners monitor their progress.
The course allows learners to study at their own pace. After completing the course, learners can take the certification exam online through a secure remote-proctored system.
Why This Certification Matters?
- Hands-on expertise Practical tools and strategies for implementing secure AI practices.
- Enhanced threat management Identify, assess, and mitigate threats such as adversarial attacks and data poisoning.
- Practical security integration Security measures integrated from design through deployment and monitoring.
- Real-world case studies Actionable insights from industry case studies on AI security challenges.
- Continuous learning Stay current on emerging technologies and best practices.
What You'll Learn?
Overview of AI Security Challenges
Secure Design Principles
Best Practices for Secure AI
Hands-On: Threat Modeling Workshop
Introduction to Threat Modeling
Creating an AI Threat Model
Tools for Threat Modeling
Case Study: AI in Autonomous Vehicles
SDLC Overview
AI-Specific Security Measures
Continuous Monitoring & Feedback Loops
Hands-On: Integrating Security in AI Development
Use Case: AI Fraud Detection System
Securing AI Systems Post-Deployment
Model Integrity and Auditing
Hands-On: Implementing RBAC
Preparing AI Systems for Audits
Red-Teaming for AI Systems
Hands-On: Red-Teaming Simulation
Introduction to AI Security Tools
Automating AI Security and Compliance
Hands-On: Tool Integration
Job Roles & Industry Outlook
AI Security Professionals
Build practical skills in securing AI systems and managing risk across the AI lifecycle.
Data Scientists and Engineers
Integrate security into AI model development and deployment pipelines.
AI Governance and Compliance Officers
Understand security measures and regulatory requirements for AI systems.
Tech Leads and Managers
Ensure secure and ethical AI practices within AI project teams.
Cybersecurity Experts
Specialize in AI-specific threats, threat modeling, and risk mitigation.
Skills You’ll Gain
Tools You’ll Master