Practitioner’s Playbook for RSAIF - eLearning (exam included)
275,00 EUR
- 16 hours
Master Responsible & Secure AI Implementation Take your AI security expertise to the next level with the Practitioner’s Playbook for RSAIF — a hands‑on, practical program designed to equip you with the tools, strategies, and frameworks needed to secure AI systems across their lifecycle. This course goes beyond concepts to show you how to identify and mitigate AI‑specific threats such as adversarial attacks, model drift, and data poisoning, and how to integrate security best practices into every stage from design through deployment and monitoring.
Key Features
Language
Course and material in English
Level
Beginner-Intermediate level
Access
1 year access to the platform 24/7
8 hours of video lessons & multimedia
16 hours of study time recommendation
eBooks, Audiobooks, Podcasts
Quizzes, Assessments, and Course Resources
Exam
Online Proctored Exam with One Free Retake
Certificate
Certification of completion included
Learning Outcomes
At the end of this course, you will be able to:
AI System Protection
Acquire practical skills to secure AI systems across the full development lifecycle, from design to deployment.
Threat Detection & Mitigation
Learn to identify and counter AI-specific risks such as adversarial attacks, model drift, and data poisoning
AI Governance & Compliance
Gain mastery of AI governance frameworks and regulatory standards, including GDPR, NIST, and the EU AI Act.
Security Tool Implementation
Build hands-on expertise in deploying security tools for continuous monitoring and protection of AI systems
Applied Case Studies
Explore real-world examples to understand and address security challenges in AI applications
Course timeline
Responsible Development & Secure Design
Lesson 1
- Overview of key AI security challenges
- Principles for designing secure AI systems
- Best practices for building resilient AI solutions
- Hands-on workshop: Threat modeling
AI Threat Models
Lesson 2
- Introduction to AI-specific threat modeling
- Creating actionable AI threat models
- Tools to support threat modeling
- Case study: Securing AI in autonomous vehicles
Secure AI Software Development Lifecycle (SDLC)
Lesson 3
- Overview of SDLC for AI projects
- Implementing AI-specific security measures
- Continuous monitoring and feedback loops
- Hands-on: Integrating security in AI development
- Use case: AI-driven fraud detection system
Enforcement & Model Integrity
Lesson 4
- Securing AI systems after deployment
- Model auditing and integrity assurance
- Hands-on exercise: Role-Based Access Control (RBAC)
Audit Readiness & Red-Teaming
Lesson 5
- Preparing AI systems for audits
- Conducting red-teaming exercises for AI security
- Hands-on simulation: Red-teaming AI systems
Toolkits & Automation
Lesson 6
- Introduction to AI security tools
- Automating security and compliance workflows
- Hands-on: Tool integration for continuous AI protection
Industry Growth
- The global AI cybersecurity market is expected to surge from USD 30.92 billion in 2025 to USD 86.34 billion by 2030, growing at a 22.8% CAGR (Mordor Intelligence).
- Organizations are rapidly adopting AI-driven security solutions to tackle increasingly sophisticated cyber threats, boosting demand for skilled AI security professionals.
- Leading cybersecurity companies are expanding their offerings to include AI-focused certifications, reflecting the industry’s strategic pivot toward AI-specific security challenges.
- The proliferation of AI technologies has introduced new vulnerabilities, creating a need for certified experts who can implement robust AI security measures.
- As AI systems become more complex, there is a strong emphasis on continuous learning to stay ahead of evolving threats and innovative security solutions.
Who Should Enroll in this Program?
AI Security Professionals: Enhance hands-on expertise in protecting AI systems and managing risks throughout the AI lifecycle.
Data Scientists & AI Engineers: Learn to embed security best practices directly into AI model development and deployment workflows.
AI Governance & Compliance Officers: Gain deeper insights into regulatory requirements and security measures for AI systems.
Tech Leads & Project Managers: Ensure secure, ethical, and resilient AI practices within your teams and projects.
Cybersecurity Specialists: Develop advanced skills to address AI-specific threats and strengthen risk mitigation strategies.
More Details
Prerequisites
- Hands-On Security Focus: Designed for professionals, the course emphasizes practical strategies, enabling participants to apply advanced tools and frameworks to safeguard AI systems.
- Experience with Security Tools: Engage directly with tools for threat modeling, adversarial testing, and monitoring to gain real-world experience in protecting AI models.
- Interactive Learning & Application: Through live sessions and collaborative exercises, participants develop actionable security plans to defend AI systems against real-world threats.
- Advanced Self-Paced Modules: After live sessions, self-paced content dives deeper into complex AI security concepts, reinforcing learning and mastery of practical security frameworks.
Exam Details
- Duration: 90 minutes
- Passing :70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
- Language: English
Licensing and accreditation
This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
Frequently Asked Questions
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