Learning Outcomes

In this free course, you will learn how to:

• Discuss basic machine learning concepts and how they are used to detect and prevent cybersecurity threats
• Analyze supervised learning techniques for threat detection and improving cybersecurity outcomes
• Apply unsupervised learning methods to identify anomalies and detect cyber threats
• Evaluate the effectiveness of adversarial machine learning techniques in overcoming adversarial attacks
• Assess the effectiveness of model evaluation and validation in machine learning solutions for cybersecurity
• Outline neural networks and their role in solving complex cybersecurity challenges
• Describe how to use convolutional neural networks (CNNs) for threat analysis and enhancing cybersecurity systems
• Explain recurrent neural networks (RNNs) and how they can be used in cyber defense applications
• Recognize anomalies, malware and unusual activities in systems and data to detect and prevent cyber attacks
• Recall the challenges and limitations of deep learning models in real-world cybersecurity implementations
• Combine machine learning and deep learning techniques to revolutionize and enhance modern cybersecurity defenses