| Category | AI Security, AI Technical, All Courses, Available Now, English, Ethical Hacker / Penetration Tester, Expert, Language, Network Security Engineer |
|---|---|
| Program Name | AI+ Security Level 3™ |
| Duration | Instructor-Led:5 Days (live or virtual) | Self-Paced:40 hours of content |
| Prerequisites | Completion of AI+ Security Level 1™ and 2™ Intermediate/Advanced Python Programming: Proficiency or expert in Python, including deep learning frameworks (TensorFlow, PyTorch). Intermediate Machine Learning Knowledge: Proficiency in understanding of deep learning, adversarial AI, and model training. Advanced Cybersecurity Knowledge: Proficiency in threat detection, incident response, and network/endpoint security. AI in Security Engineering: Knowledge of AI’s role in identity and access management (IAM), IoT security, and physical security. Cloud and Container Expertise: Understanding of cloud security, containerization, and blockchain technologies. Linux/CLI Mastery: Advanced command-line skills and experience with security tools in Linux environments |
| Exam Format | 50 questions, 70% passing, 90 minutes, online proctored exam |
Acquire expertise in using deep learning algorithms for advanced applications like malware analysis, phishing detection, and predictive threat modeling.
Understand the use of AI for securing cloud-based platforms and containerized applications, focusing on scalability and automation in threat mitigation.
Learn to apply AI techniques to streamline identity verification, manage access control systems, and secure authentication processes.
Explore how AI can be used to address unique IoT security challenges, including detecting compromised devices and protecting communication protocols.
Develop Al-powered IAM solutions to improve access control, and identity verification processes for large-scale organizations.
Advise on implementing AI-driven security technologies, offering best practices and system integration for optimal protection.
Use Al to protect IoT devices and networks, ensuring the security of interconnected systems in industries like healthcare, manufacturing, and smart cities.
Leverage Al to enhance cloud security, focusing on areas like container security, threat detection, and incident response in cloud environments.
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.
70%
50 multiple-choice/multiple-response questions
