Supervised learning models identify and mitigate cybersecurity threats by leveraging labeled datasets to train algorithms. In this course, you’ll explore a range of machine learning and deep learning tools and techniques, including supervised and unsupervised learning, to effectively detect, prevent, and respond to cyber threats. Additionally, you’ll learn how to identify unusual activities, detect malware, and block harmful links to safeguard your models and data from unauthorized access.

Neural networks, inspired by the human brain, are trained with large datasets to learn complex patterns and relationships. You’ll learn how to use the power of neural networks to detect deviations from normal patterns, handle and analyze large volumes of data with high accuracy and address sophisticated threats. We demonstrate how convolutional and recurrent neural networks can be utilized for threat analysis to strengthen cyber defense against evolving cyber-attacks.

We designed this course for cybersecurity professionals, data scientists, and anyone interested in using AI to combat cyber threats. Completion of 'AI-Powered Cybersecurity Fundamentals' is a mandatory prerequisite for this course to ensure you have the foundational knowledge required for advanced topics. This course features case studies and real-world examples to showcase the practical use of deep learning and machine learning techniques in cyber defense. Enroll now to master the key tools for enhancing cybersecurity defenses.