Mastering Generative AI for Cybersecurity
Apply generative AI to cybersecurity including UEBA, threat intelligence, phishing detection, malware analysis, and protection against digital threats.
Apply generative AI to cybersecurity including UEBA, threat intelligence, phishing detection, malware analysis, and protection against digital threats.
This comprehensive course explores how generative AI is transforming cybersecurity by enabling faster threat detection, proactive defense strategies, and advanced solutions against sophisticated attacks. Designed for both existing and aspiring cybersecurity professionals, it builds valuable skills in generative AI techniques and tools to effectively handle complex security challenges. Throughout the course, participants learn to explore undetected vulnerabilities using AI and machine learning while mastering foundational principles of generative AI and their practical applications in cybersecurity. Key focus areas include user and entity behavior analytics (UEBA), threat intelligence, report summarization, automated playbooks, and countering various threats like phishing, malware, misinformation, and deepfakes. The curriculum also covers natural language processing attack techniques such as prompt injection and relevant countermeasures. Students will discover how generative AI transforms Security Information and Event Management (SIEM) and Security Operations Center (SOC) workflows, enhancing incident response, threat detection, and vulnerability management. The course includes practical exercises, hands-on labs, and a final project for applying learned skills, making it ideal for professionals looking to add in-demand generative AI capabilities to their cybersecurity expertise.
Instructors:
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What you'll learn
Leverage generative AI in cybersecurity applications including UEBA, threat intelligence, report summarization, and automated playbooks
Implement AI-driven approaches to counter cybersecurity threats like phishing, malware, misinformation, and deepfakes
Streamline SIEM and SOC tasks with generative AI to optimize operational efficiency and threat management
Integrate generative AI in critical cybersecurity operations such as incident response, threat detection, and vulnerability management
Develop strategies to guard against NLP-based attacks on generative AI systems
Apply machine learning techniques for enhanced pattern recognition in cybersecurity data
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Quizzes, Final Project, Final Exam
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 3 modules in this course
This course explores the transformative impact of generative AI on cybersecurity practices. It covers how AI technologies can enhance threat detection, vulnerability management, and defense strategies against sophisticated cyber attacks. Participants learn to apply generative AI techniques to critical cybersecurity domains including user and entity behavior analytics, threat intelligence generation, report summarization, and automated response playbooks. The curriculum addresses practical applications in countering modern threats such as phishing, malware, misinformation, and deepfakes. Special attention is given to natural language processing attack techniques like prompt injection and their countermeasures. The course demonstrates how generative AI can optimize Security Information and Event Management (SIEM) and Security Operations Center (SOC) workflows, improving incident response efficiency and threat management capabilities. Through hands-on labs and practical exercises, participants develop skills in integrating AI tools into cybersecurity operations while considering ethical implications and potential risks of these technologies. The program culminates in a final project where students apply their knowledge to real-world cybersecurity scenarios.
Get Started with Generative AI in Cybersecurity
Module 1
SIEM and SOC Tasks Using Generative AI
Module 2
Final Project and Exam
Module 3
Fee Structure
Payment options
Financial Aid
Instructor
Technology Education and Skills Development Leader at IBM
Rav Ahuja serves as the Chief Content Officer and Global Program Director at IBM Skills Network, where he leads curriculum creation, growth strategy, and partner programs. After earning his B.Eng. from McGill University and MBA from the University of Western Ontario, he co-founded Cognitive Class, an IBM initiative focused on democratizing access to in-demand technology skills. Based at the IBM Canada Lab in Toronto, he specializes in developing instructional solutions for AI, Data Science, Cloud Computing, and Cybersecurity. His impact on technology education is evidenced through his role as architect of numerous IBM Professional Certificates and instructor for over 35 online courses, including popular offerings like "What is Data Science?", "Introduction to Cloud Computing," and "Introduction to Artificial Intelligence (AI)." His courses have reached hundreds of thousands of learners worldwide, with "What is Data Science?" alone enrolling over 638,000 students. His recent work includes developing new Generative AI courses and career guidance content for IBM's Professional Certificate programs, demonstrating his ongoing commitment to preparing learners for emerging technology careers
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