Generative AI skills are becoming an essential part of a cybersecurity professional’s toolkit. The US Bureau of Labor Statistics projects a 32% increase in the number of cybersecurity professionals needed through 2032, with a current median salary of $112,000. This Specialization is designed to build skills enabling you to enter this lucrative and exciting field.

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, andothers. You’ll explore popular prompt engineering tools including IBM Watsonx, Prompt Lab, Spellbook, and Dust.

Then dive intofundamental concepts of generative AI usefor cybersecurity. Gain valuable job 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 toidentify 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. 

Applied Learning Project

This Specialization emphasizes applied learning and includes a series of hands-on activities and projects. In these exercises, you’ll take the theory and skills you’ve gained and practice them with real-world scenarios. 

Projects include:

• Generate Text, Images, and Code using Generative AI

• Apply Prompt Engineering Techniques and Best Practices’

• Use Generative AI in Cybersecurity for content filtering, threat analysis, and automated response generation