Certified Professional in AI Security (CAIS)

The Certified Professional in AI Security and Machine Learning Defense (CAIS) is an intensive 2-month program that transforms cybersecurity professionals into AI security specialists capable of defending against sophisticated adversarial attacks.

You’ll master both offensive red team techniques and defensive blue team strategies specific to AI/ML systems, from adversarial attacks and model poisoning to runtime monitoring and privacy-enhancing technologies.

Key Features of the Program

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Heisenberg Institute CAIS Professional Certification

Industry-recognized credential in AI/ML cybersecurity
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Offensive AI Security Masterclass

Hands-on adversarial attack techniques and red team methodologies
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World-Class Faculty

Learn from former AI security researchers and penetration testing specialists
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Practical Attack Portfolio

Execute simulated adversarial attacks and build defensive frameworks
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Industry-Standard Tools Mastery

Hands-on experience with Adversarial Robustness Toolbox (ART), CleverHans, Foolbox, ModelScan, and AI security frameworks
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CTF and Red Team Training

Participate in AI-focused Capture The Flag competitions and red team exercises
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Career Acceleration Support

Dedicated career services for highly specialized AI security roles
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Cutting-Edge Curriculum

Stay current with the latest AI security risks including strong data validation, model security, and ethical AI practices
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15X Higher Practical Application

Unique hands-on program with adversarial attack simulation and defense implementation
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Flexible Learning Options

Live online masterclasses on Friday’s and Saturday’s with recorded sessions and virtual lab access

WHO IS THIS PROGRAM FOR

CYBERSECURITY PROFESSIONALS

  • Security Engineers Specializing in AI/ML Defense
  • Penetration Testers Expanding to AI Attack Vectors
  • Security Analysts Adding AI Threat Intelligence
  • Incident Responders Handling AI Security Breaches

TECHNICAL & LEADERSHIP ROLES

  • Security Architects Designing AI Security Strategies
  • CISO Teams Building Enterprise AI Defenses
  • MLOps Engineers Securing ML Pipelines
  • AI Developers Building Inherently Secure Systems

ADVANCED SPECIALISTS

  • Red Team Specialists Targeting AI Systems
  • Blue Team Defenders Protecting ML Models
  • Government & Defense Security Professionals
  • Threat Researchers Studying AI Vulnerabilities

WHY HEISENBERG

50+

Partners across Universities, Research Institutes and AI Companies

Access unparalleled opportunities through our extensive network spanning academia and industry, providing diverse perspectives and real-world connections throughout your learning journey.

12

Weeks of Internship training

Apply classroom knowledge immediately in structured internships with leading AI companies, where you’ll solve actual business challenges alongside industry professionals.

18

industry experts contributing to curriculum design and mentorship

Learn directly from AI practitioners who’ve implemented solutions at scale. Our experts shape curriculum content and provide personalized guidance throughout your training.

3x

faster skill acquisition rate compared to other training entities

Our immersive methodology accelerates learning through guided practice and immediate application, helping you master complex AI concepts and implementations in record time.

24/7

access to learning resources and support community

Never hit a roadblock with our always-available learning platform and vibrant community of peers, mentors, and alumni ready to help anytime.

Certification

Upon successful completion of the program, participants will receive the Certified Professional in AI Security and Machine Learning Defense (CAIS) credential from the Heisenberg Institute for AI and Quantum Computing

  • Professional Credential: validating hands-on expertise in adversarial attacks, model hardening, and AI threat defense
  • Elite Career Positioning: for specialized roles as AI Security Engineers, ML Security Architects, and Red Team Specialists
Heisenberg Institute's Sample Certificate

LEARNING PATH

The program is structured into three distinct phases to ensure a seamless learning journey.

Phase 1 (Week 1-2)
Foundations of AI Security & Threat Modeling
  • ML Lifecycle Security Framework: Vulnerability identification across data collection, model training, deployment, and inference phases.
  • AI Threat Taxonomy: Comprehensive classification of attacks targeting integrity, confidentiality, availability, and robustness.
  • Risk Assessment Methodologies: Enterprise-level AI security risk evaluation and threat modeling.
  • AI Security Tool Ecosystem: Hands-on introduction to ART, CleverHans, Foolbox, and testing environments.
  • Responsible AI Security Integration: Ethical considerations as security enablers in ML systems.
  • Threat Intelligence for AI Systems: Understanding attacker motivations, capabilities, and attack surfaces.

Phase 2 (Weeks 3-5)
Offensive AI Security - Red Team Techniques
  • Adversarial Evasion Attacks: Execute FGSM, C&W, PGD, and advanced perturbation techniques on ML models.
  • Data Poisoning & Backdoor Attacks: Training data manipulation and trojan implementation methodologies.
  • Model Extraction & Inversion: Intellectual property theft and data reconstruction attack techniques.
  • Generative AI Attacks: Prompt injection, jailbreaking, and LLM manipulation strategies.
  • Membership Inference Attacks: Privacy violation through training data extraction techniques.
  • Custom Attack Development: Building novel adversarial techniques for specific target architectures.
  • AI Penetration Testing: Systematic approach to ML system security assessment and vulnerability analysis.
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Phase 3 (Weeks 6-8)
Defensive Strategies & Model Hardening
  • Adversarial Defense Techniques: Adversarial training, gradient masking, and input transformation for model resilience.
  • Data Security & Validation: Anomaly detection, source verification, and feature store protection systems.
  • Model IP Protection: Watermarking, fingerprinting, and unauthorized usage detection mechanisms.
  • Runtime Security Monitoring: Baseline establishment, drift detection, and anomaly alerting for production AI.
  • Secure Inference Architecture: API security, container hardening, and secrets management for ML systems.
  • Privacy-Enhancing Technologies: Differential privacy, federated learning, and homomorphic encryption implementation.
  • AI Incident Response: Playbooks for adversarial attacks, model failures, and data breach scenarios.

Program Eligibility Requirements

This is a highly selective program with only 20 candidates accepted per cohort through a rigorous evaluation process. Applications are reviewed holistically, considering motivation, and potential for growth in the AI field. Given the limited seats available, early application is strongly encouraged

Selection Criteria

  • Statement of purpose demonstrating genuine interest in AI and career goals
  • 5+ years of experience in Information Security or related field (OR)
  • A bachelor’s degree or final year (undergraduate or postgraduate students) with an average of 50% or higher marks in Cybersecurity or related field (OR)
  • Candidates certified in CISA, CISSP, CISM certification
  • Personal interview assessing motivation, learning ability, and cultural fit
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Cohort Commencement Dates

The CAIG program admits a limited number of candidates per cohort. Review the intake schedule below and apply early to secure your seat in the next session.

Cohort Application Closes Program Starts
Winter Cohort December 15, 2025 January 15, 2026
Spring Cohort April 20, 2026 May 1, 2026
Summer Cohort June 15, 2026 July 15, 2026
Fall Cohort September 15, 2026 October 15, 2026

Note:
Applicants are encouraged to apply 6–8 weeks prior to the deadline.

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Full Program Fee: USD 1,499

Invest in elite AI security expertise with an intensive certification combining offensive red team techniques and defensive strategies that positions you at the forefront of the most critical cybersecurity specialization

Your Value Includes:

  • Certified Professional in AI Security and Machine Learning Defense (CAIS) — industry-recognized credential awarded by the Heisenberg Institute for AI and Quantum Computing
  • Offensive & Defensive Security Masterclasses — live expert-led training in adversarial attacks, model poisoning, and ML system defense strategies
  • Real-World Attack Simulation Portfolio — hands-on experience executing penetration tests and building security frameworks for AI/ML systems

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