AI+ Security Strategist™
AT-2103
Formerly known as AI+ Security Level 3™Validate Your Expertise in Cybersecurity
This certification validates advanced-level expertise in AI-driven cybersecurity strategy, governance, and risk management. The exam assesses deep knowledge of advanced security architectures, AI-enabled threat intelligence, and strategic security decision-making within complex enterprise environments.
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Who Should Enroll?
Cybersecurity Professionals: Individuals looking to enhance their skills in compliance and security management.
Risk Management Specialists: Those interested in improving risk assessment and mitigation strategies using AI.
Compliance Officers: Professionals responsible for ensuring adherence to regulatory standards who want to leverage AI for compliance processes.
IT Security Analysts: Analysts seeking to integrate AI technologies into their security practices and frameworks.
Ethical Hackers and Penetration Testers: Individuals wanting to explore AI techniques for identifying vulnerabilities, defending against adversarial attacks, and stress-testing systems.
Tech-Savvy Leaders: IT managers or security architects aiming to future-proof their organizations with AI-enhanced compliance, governance, and security practices.
Aspiring AI Security Experts: Learners with foundational knowledge in AI and cybersecurity eager to master AI-powered solutions for emerging threats and advanced security challenges.
Job Roles & Industry Outlook
AI Security Analyst
Uses AI techniques for threat detection, security analysis, and risk identification.
Cybersecurity Engineer
Implements AI-powered security solutions and defense strategies.
SOC Analyst
Uses AI tools for security monitoring, investigation, and incident response.
AI Threat Intelligence Analyst
Identifies emerging threats using AI-driven analysis.
Cloud Security Engineer
Applies AI solutions to protect cloud environments.
Penetration Tester
Uses AI-based techniques to identify vulnerabilities.
Security Consultant
Advises organizations on AI-driven cybersecurity strategies.
Skills You'll Gain
- AI-driven cybersecurity strategy and risk management
- Designing AI-powered security frameworks and defense strategies
- Security governance, compliance, and responsible AI practices
- AI threat modeling and cybersecurity risk assessment
- Evaluating AI security tools and technologies
- Developing organizational AI security adoption strategies
- Managing AI-related risks, policies, and controls
- Integrating AI into enterprise security operations
- Building secure and resilient AI-driven environments
- Making strategic cybersecurity decisions using AI insights
What You'll Learn
- This module equips you to implement cutting-edge AI-driven security solutions. You’ll explore core algorithms like neural networks, advanced NLP techniques, and deep learning models to analyze security logs. The module also guides you on designing AI pipelines, managing imbalanced datasets, and mitigating adversarial threats, ensuring that your security systems remain adaptive and robust against evolving cyber risks.
- This module provides practical expertise in applying supervised and unsupervised learning methods for tasks such as malware classification, anomaly detection, and real-time threat response. You’ll also learn to build advanced pipelines, optimize AI models, and use tools like Apache Kafka and Spark for scalable real-time solutions.
- In this module, you’ll gain proficiency in implementing CNNs, RNNs, and hybrid models for network traffic classification, phishing detection, and intrusion analysis. Additionally, you’ll explore autoencoders for anomaly detection and adversarial training methods to strengthen defenses against manipulated inputs.
- This module explores the strategies for crafting secure AI systems, including adversarial training, ensemble methods, and red teaming. You’ll also explore tools for simulating attacks and designing architectures that resist adversarial inputs while maintaining transparency and trust.
- This module teaches you to implement AI-powered IDS, anomaly detection models, and zero-trust architectures. With case studies and hands-on projects, you’ll develop skills in integrating AI into next-generation firewalls and optimizing network security for high-throughput environments.
- In this module, you’ll learn to build AI-based malware detection systems, optimize models for polymorphic threats, and leverage ML for anomaly detection on endpoints. The content also covers securing IoT devices and implementing lightweight AI solutions for resource-constrained environments.
- This module provides expertise in designing robust AI pipelines, incorporating cryptographic techniques, and optimizing models for real-time security. You’ll also explore frameworks for ensuring explainability, scalability, and compliance with data protection regulations.
- This module equips you to build AI systems for cloud security, integrate tools into container orchestration platforms like Kubernetes, and deploy AI-driven solutions for serverless architectures. You’ll also explore DevSecOps practices and advanced security testing methods.
- This module offers insights into integrating AI with blockchain for transaction security, optimizing consensus mechanisms, and safeguarding smart contracts. Practical case studies showcase applications in cryptocurrency exchanges and supply chain management.
- This module focuses on automating role-based access controls, detecting unauthorized access, and implementing AI-driven MFA systems. You’ll also explore real-world applications of reinforcement learning and AI-based fraud detection in IAM scenarios.
- This module covers AI solutions for securing smart cities, industrial IoT, and autonomous vehicles. You’ll also learn about federated learning for decentralized security and techniques for safeguarding smart home devices against unauthorized access.
- This module guides you through every step, from defining project goals and selecting datasets to integrating AI models into existing infrastructures. You’ll gain hands-on expertise in creating scalable, adaptive, and effective security solutions.
Tools You'll Explore
Splunk UBA
Microsoft Defender for Endpoint
Microsoft Azure AD Conditional Access
Adversarial Robustness Toolkit (ART)
CrowdStrike Falcon XDR
Palo Alto Cortex XDR
Darktrace Enterprise
Vectra for Cloud
Fortinet AI Cloud Security
Semgrep
Prerequisites
- Foundation in AI+ Security: Completion of AI+ Security Compliance Practitioner and AI+ Security Practitioner.
- Intermediate / Advanced Python Programming: Proficiency in Python, including experience with deep learning tools like TensorFlow and PyTorch.
- Advanced Cybersecurity Knowledge: Strong skills in threat detection, incident response, and securing networks and devices.
- Cloud and Blockchain Basics: Understanding of cloud security, container systems, and blockchain technology.
- Linux/CLI Mastery: Advanced command-line skills and experience with security tools in Linux environments.
- AI in Security Engineering: Knowledge of AI’s role in identity and access management (IAM), IoT security, and physical security.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50 Correct)
Format
Multiple Choice Questions (MCQ)
Delivery Method
Online via proctored exam platform
Exam Blueprint:
- Foundations of AI and Machine Learning for Security Engineering - 5%
- Machine Learning for Threat Detection and Response - 5%
- Deep Learning for Security Applications - 5%
- Adversarial AI in Security - 6%
- AI in Network Security - 6%
- AI in Endpoint Security - 8%
- Secure AI System Engineering - 8%
- AI for Cloud and Container Security - 11%
- AI and Blockchain for Security - 11%
- AI in Identity and Access Management (IAM) - 12%
- AI for Physical and IoT Security - 12%
- Capstone Project - Engineering AI Security Systems - 11%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
Instructor-Led (Live Virtual/Classroom)
- 5 days of intensive training with live demos
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- ~40 hours of on-demand video lessons, e-book, podcasts, and interactive labs
- Learn anywhere, anytime, with modular quizzes to track progress
Discover Your Ideal Role-Based Certifications and Programs!
Not sure which certifications to go for? Take our quick assessment to discover the perfect role-based certifications and programs tailored just for you.
Get CertifiedFrequently Asked Questions
The certification focuses on designing and implementing advanced AI-driven security solutions across networks, cloud, endpoints, and enterprise environments.
The program covers AI engineering, threat detection, deep learning, adversarial AI, cloud security, blockchain security, IAM, and IoT protection.
The certification is designed for professionals with advanced knowledge of AI security, cybersecurity, Python, cloud, Linux, and security engineering.
Learners will gain skills in building AI security systems, optimizing models, analyzing threats, and implementing secure AI solutions.
The course explores machine learning, deep learning, adversarial AI, cloud security, blockchain, IoT security, and AI-driven IAM.
