AI+ Security Practitioner™
AT-2101
Formerly known as AI+ Security Level 1™Empowering Cybersecurity with AI
This certification validates foundational knowledge of AI-driven cybersecurity concepts and assesses understanding of security principles, threats, and controls. The exam evaluates competency in applying core cybersecurity knowledge within AI-enabled 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: Those who want to enhance their security skills by applying AI techniques for threat detection, analysis, and response.
Security Analysts: Those who work with security monitoring, incident investigation, vulnerability assessment, and AI-assisted security operations.
IT Professionals: Those who want to understand how AI can strengthen infrastructure protection, risk management, and security workflows.
Network and System Administrators: Those who manage digital environments and want to use AI tools to improve security monitoring and protection.
Risk and Compliance Professionals: Those who want to explore AI-driven approaches for security governance, compliance management, and risk assessment.
Ethical Hackers and Security Researchers: Those who want to apply AI capabilities to identify vulnerabilities, analyse threats, and improve defensive strategies.
AI and Technology Professionals: Those who want to understand the security challenges of AI systems and implement safer AI solutions.
Security Managers and Decision Makers: Those who want to leverage AI insights to improve cybersecurity strategies, operational efficiency, and organizational resilience.
Job Roles & Industry Outlook
AI Security Analyst
Protect AI systems by identifying vulnerabilities, monitoring threats, and implementing security controls across AI applications.
Cybersecurity Analyst
Monitor security events, analyze cyber threats, and safeguard enterprise networks and AI-powered environments.
SOC Analyst
Detect, investigate, and respond to security incidents using Security Operations Center (SOC) tools and AI-driven monitoring solutions.
Threat Hunter
Proactively identify advanced cyber threats, uncover hidden attacks, and strengthen organizational security through continuous threat hunting.
Security Engineer
Design, implement, and maintain secure infrastructure, applications, and AI systems to protect against evolving cyber risks.
AI Risk Specialist
Assess AI-related security risks, ensure regulatory compliance, and develop governance frameworks for responsible AI adoption.
Incident Response Analyst
Investigate cybersecurity incidents, contain threats, and coordinate recovery efforts to minimize business impact and improve resilience.
Skills You’ll Gain
- AI Security and Secure AI Deployment
- AI/ML-Based Threat Detection and Analysis
- Threat Hunting and Incident Response
- SOC Operations and Security Monitoring
- Python-Based Security Automation
- Security Data Analysis and Log Investigation
- LLM Security and AI Threat Modeling
- Vulnerability Assessment and AI Red Teaming
- Identity Security and Access Control Management
- Cryptography and Data Protection Practices
- Security Governance, Compliance, and Responsible AI
What You'll Learn
- You will learn about computer systems, operating systems, Linux administration, file systems, commands, user management, permissions, authentication, and access control concepts.
- You will learn networking concepts, IP addressing, protocols, TCP/IP communication, DNS, network security, traffic analysis, firewalls, IDS/IPS, and VPN technologies.
- You will learn Python programming fundamentals and how to use scripting for security automation, log analysis, data processing, and efficient security workflows.
- You will learn cybersecurity principles, risks, vulnerabilities, attack surfaces, security controls, common cyber threats, and industry security frameworks.
- You will learn encryption, hashing, digital signatures, TLS security, authentication methods, identity management, access controls, and identity protection practices.
- You will learn AI, ML, and Deep Learning fundamentals, learning approaches, ML lifecycle, datasets, model evaluation, and AI applications in cybersecurity.
- You will learn AI-based threat detection, behavioral analytics, anomaly detection, threat intelligence, threat hunting, MITRE ATT&CK mapping, and AI-assisted SOC operations.
- You will learn LLMs, Generative AI, AI copilots, RAG, OWASP LLM security risks, AI vulnerabilities, governance, and responsible AI practices.
- You will learn AI threat modeling, attack surfaces, adversarial attacks, STRIDE methodology, AI vulnerabilities, red teaming, and security testing approaches.
- You will learn about SOC operations, SIEM concepts, incident response, malware analysis, threat investigation, and AI-assisted security operations.
- You will learn security governance, risk management, AI governance, compliance, privacy principles, and responsible AI security practices.
- You will apply cybersecurity skills through an end-to-end AI security project involving threat analysis, AI risk assessment, incident response, and professional security reporting.
Tools You'll Explore
Scikit-learn
TensorFlow
PyTorch
Kali Linux
Wireshark
Nmap
Wazuh
Splunk
OWASP ZAP
Prerequisites
- Basic understanding of AI and cybersecurity concepts, including security principles and terminology.
- Knowledge of security operations such as threat detection, risk management, vulnerability assessment, and incident response.
- Familiarity with networking, systems, cloud environments, and security controls.
- Understanding data protection, privacy, compliance, and secure data handling practices.
- Basic programming and automation awareness for security workflows.
- Awareness of responsible AI, security governance, and AI-powered security tools.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50 Correct)
Format
Multiple Choice Questions (MCQ)
Delivery Method
Online via proctored exam platform
- Computing, Linux & Operating System Foundations - 6%
- Networking Fundamentals and Traffic Analysis - 9%
- Python for Security and Automation - 9%
- Cybersecurity Foundations and Threat Landscape - 9%
- Cryptography, Authentication & Identity Security - 9%
- Introduction to Artificial Intelligence and Machine Learning - 9%
- AI Applied to Security Detection and Threat Hunting - 9%
- AI Security, LLM Security and Responsible AI - 9%
- Offensive Security for AI Systems - 8%
- Security Operations, Incident Response and Malware Analysis - 18%
- Governance, Compliance and Ethical AI Security - 8%
- Capstone Project — AI-Driven Security Operations and Defense - 8%
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
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Get CertifiedFrequently Asked Questions
This course covers AI security, cybersecurity foundations, threat detection, AI-driven security operations, LLM security, and responsible AI practices.
This course is designed for learners with basic knowledge of AI, cybersecurity, networking, programming, security operations, and responsible AI.
The certification exam includes 50 questions, requires a 70% passing score, and has a 90-minute online proctored format.
You will gain skills in AI security, threat detection, cybersecurity operations, LLM security, automation, and responsible AI practices.
You will explore tools such as Scikit-learn, TensorFlow, PyTorch, Kali Linux, Wireshark, Nmap, Wazuh, Splunk, and OWASP ZAP.
