AI+ Security StrategistTM

An advanced-level credential that validates expertise in AI-driven cybersecurity strategy, governance, and risk management for complex enterprises.

pa-ai-security-strategist-badge

Validate Your Expertise in Cybersecurity

  • Advanced AI Defense Design:
    Build AI-powered security architectures and defense strategies for networks, cloud, endpoints, and enterprise environments
  • Hands-On Projects:
    Apply skills through projects and case studies, culminating in a capstone that engineers a complete AI security system
  • Strategic Decision-Making:
    Use AI insights to make cybersecurity leadership decisions and manage AI-related risks, policies, and controls
  • Flexible Learning:
    Choose instructor-led training or a self-paced course with about 40 hours of videos, e-book, podcasts, and labs
  • Industry-Recognized Credential:
    Earn an official exam credential and digital badge that signal readiness for CISO-level leadership

Prerequisites

  • Completion of AI+ Security Compliance Practitioner and AI+ Security Practitioner
  • Intermediate to advanced Python, including experience with TensorFlow and PyTorch
  • Advanced cybersecurity knowledge in threat detection, incident response, and securing networks and devices
  • Understanding of cloud security, container systems, and blockchain technology
  • Advanced Linux and command-line skills with security tools
  • Knowledge of AI’s role in identity and access management, IoT security, and physical security

Why This Certification Matters?

  • IoT Security Using AI: Demonstrates advanced competency in AI-powered security architectures and controls.
  • Deep Learning Algorithms: Includes advanced scenario-based assessments focused on strategic cyber defense decisions.
  • AI-Driven Network Security: Presents advanced exam scenarios focused on enterprise-level security challenges.
  • Endpoint Protection with AI: Validates readiness for executive and CISO-level cybersecurity leadership roles.

What You'll Learn?

1.1 Neural networks, advanced NLP, and deep learning for analyzing security logs, plus imbalanced datasets and adversarial threats

2.1 Supervised and unsupervised learning for malware classification, anomaly detection, and real-time response with Kafka and Spark

3.1 CNNs, RNNs, and hybrid models for traffic classification, phishing detection, intrusion analysis, and autoencoders

4.1 Adversarial training, ensemble methods, red teaming, attack simulation, and architectures that resist adversarial inputs

5.1 AI-powered IDS, anomaly detection, zero-trust architectures, and integration with next-generation firewalls

6.1 AI-based malware detection, models for polymorphic threats, endpoint anomaly detection, and IoT and lightweight AI

7.1 Robust AI pipelines, cryptographic techniques, real-time model optimization, explainability, and data protection compliance

8.1 AI cloud security systems, Kubernetes integration, serverless security, DevSecOps, and advanced security testing

9.1 AI and blockchain for transaction security, consensus optimization, smart contract safeguards, and supply chain cases

10.1 Automated role-based access, unauthorized access detection, AI-driven MFA, reinforcement learning, and fraud detection

11.1 AI for smart cities, industrial IoT, autonomous vehicles, federated learning, and smart home device protection

12.1 Defining goals, selecting datasets, integrating AI models into infrastructure, and building scalable security solutions

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 ManagementDesigning AI-Powered Security Frameworks and Defense StrategiesSecurity Governance, Compliance, and Responsible AI PracticesAI Threat Modeling and Cybersecurity Risk AssessmentEvaluating AI Security Tools and TechnologiesDeveloping Organizational AI Security Adoption StrategiesManaging AI-Related Risks, Policies, and ControlsIntegrating AI into Enterprise Security OperationsBuilding Secure and Resilient AI-Driven EnvironmentsMaking Strategic Cybersecurity Decisions Using AI Insights

Tools You’ll Master

Splunk UBAMicrosoft Defender for EndpointMicrosoft Azure AD Conditional AccessAdversarial Robustness Toolkit (ART)CrowdStrike Falcon XDRPalo Alto Cortex XDRDarktrace EnterpriseVectra for CloudFortinet AI Cloud SecuritySemgrep

Exam Details

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

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%

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 
  • Access for Tablet & Phone