IBM Generative AI for Cybersecurity Professionals – Specialization

I completed IBM’s Generative AI for Cybersecurity Professionals specialization on Coursera in January 2025. The three courses covered generative AI, prompt engineering and uses of AI in security work.

The labs included tasks such as summarising logs, drafting vulnerability reports and preparing security documentation. They also covered the need to check model output and consider bias and explainability.

Category

Information Security / Cybersecurity / Artificial Intelligence

Issued By

IBM Skills Network

Platform

Coursera

Completion Date

09th January 2025

Verification Link

Topics covered

  • Generative AI models, including transformers and diffusion models.
  • Prompt writing and context for security analysis and documentation.
  • Using AI to summarise vulnerabilities, alerts and incident information.
  • Responsible AI use, bias, explainability and governance.
  • Lab exercises using Python and IBM watsonx.

The three courses

Generative AI: Introduction and Applications

An introduction to how generative models produce text, images and audio, and where these capabilities can be used.

Generative AI: Prompt Engineering Basics

Practice with prompts, context and model settings. I used the lab exercises to explore security reporting and risk assessment tasks.

Generative AI: Boost Your Cybersecurity Career

Exercises involving threat analysis, incident summaries and security awareness content, using simulated security scenarios.

Course Completion Certificates

Generative AI - Introduction and Applications

Generative AI - Introduction and Applications

Course 1 of 3

Generative AI - Prompt Engineering Basics

Generative AI - Prompt Engineering Basics

Course 2 of 3

Generative AI - Boost Your Cybersecurity Career

Generative AI - Boost Your Cybersecurity Career

Course 3 of 3

What I learned

I practised using AI for security documentation and analysis, and learned how prompt wording and context affect the result. I also studied the limits of these tools and why their output needs review.

This course sits alongside my work in AI governance. It gave me experience using the tools whose access, data handling and oversight controls I now review.