AI for Cybersecurity

Overview

This Specialization is designed for post-graduate students aiming to master AI applications in cybersecurity. Through three comprehensive courses, you will explore advanced techniques for detecting and mitigating various cyber threats.

The curriculum covers essential topics such as AI-driven fraud prevention, malware analysis, and the implications of Generative Adversarial Networks (GANs). You will gain hands-on experience in identifying anomalies in network traffic, implementing reinforcement learning techniques for adaptive security measures, and evaluating AI model performance against real-world challenges.

By completing this Specialization, you will develop a deep understanding of how to secure AI systems while addressing the complexities of adversarial attacks. This knowledge will prepare you to tackle emerging cybersecurity challenges, making you a valuable asset in the rapidly evolving field of digital security.

With a focus on practical applications and industry-relevant skills, you will be well-equipped for a career in AI-driven cybersecurity.

University:

Johns Hopkins University

Provider:

Coursera

Categories:

Artificial Intelligence Courses, Machine Learning Courses, Reinforcement Learning Courses, Anomaly Detection Courses, Cybersecurity Courses, Network Security Courses, Malware Analysis Courses

Subjects