
Category | AI Security |
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Program Name | AI+ Security Level 3™ |
Prerequisites |
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Exam Format | 50 questions, 70% passing, 90 Minutes |
You will learn how AI and machine learning enhance cybersecurity, including threat detection, network security, adversarial AI defense, secure AI systems, cloud security, and more. You'll also apply these concepts in a hands-on capstone project.
The course explores the use of AI to enhance blockchain security, such as fraud detection and transaction monitoring, as well as its application in securing containerized environments by automating threat detection and improving system reliability.
Basic programming knowledge is helpful, especially in Python, as the course involves implementing AI models. However, tutorials and resources are provided to help you learn necessary coding skills throughout the course.
Yes, if you're already working in cybersecurity, this course will deepen your expertise in integrating AI for advanced threat detection, automating security protocols, and strengthening defenses across networks, endpoints, and cloud systems.
While the course is designed for individuals with an intermediate level of experience in cybersecurity, it offers foundational insights into AI, making it accessible for learners looking to specialize in AI-driven security solutions.
90 Minutes
70%
50 multiple-choice/multiple-response questions
Foundations of AI and Machine Learning for Security Engineering | 6% |
Machine Learning for Threat Detection and Response | 7% |
Deep Learning for Security Applications | 7% |
Adversarial AI in Security | 10% |
AI in Network Security | 10% |
AI in Endpoint Security | 10% |
AI in Identity and Access Management (IAM) | 10% |
AI for Physical and IoT Security | 10% |
Capstone Project - Engineering AI Security Systems | 10% |
Splunk User Behavior Analytics (UBA)
Microsoft Defender for Endpoint
Microsoft Azure AD Conditional Access
Adversarial Robustness Toolbox (ART)