IBM Generative AI for Cybersecurity Professionals
About this course
Generative AI skills are becoming an essential part of a cybersecurity professional’s toolkit. Begin by learning how to distinguish generative AI from discriminative AI. You’ll explore real-world generative AI use cases and discover popular generative AI models and tools for text, code, image, audio, and videos. Next, delve into generative AI prompts engineering concepts, their real-world business uses, and prompt techniques like zero-shot and few-shot, and others. You’ll explore popular prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust. Then dive into fundamental concepts of generative AI use for cybersecurity. Gain valuable job-ready skills when you apply generative AI techniques to real-world scenarios, including UBEA, threat intelligence, report summarization, and playbooks, and assess their impact and vulnerabilities. Learn how generative AI models can help mitigate attacks, analyze real-world case studies, and learn to identify key implementation factors. Throughout your learning journey, you’ll create a project portfolio to share your provable skills with potential employers. And earn a shareable course certificate and badge that verifies your achievement.
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What you'll learn
- Distinguish between generative AI and discriminative AI
- Explore real-world use cases for generative AI in cybersecurity
- Apply prompt engineering techniques to generate relevant results
- Utilize tools for text, code, image, audio, and video generation
- Assess the impact of generative AI on cybersecurity vulnerabilities
- Create a project portfolio to demonstrate acquired skills
Course objectives
- Equip students with job-ready skills in generative AI for cybersecurity
- Enable practical application of AI techniques to real-world cybersecurity challenges
- Foster understanding of prompt engineering and its implications for business
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