Artificial Intelligence (AI) and Machine Learning (ML) in Cybersecurity

Artificial intelligence and machine learning is a rapidly growing field at the intersection of computer science and statistics concerned with finding patterns in data. It is responsible for tremendous advances in technology, from personalized product recommendations to speech recognition in cell phones. This course provides a broad introduction to the key ideas in machine learning, with a focus on applications and concepts relevant to cybersecurity. The emphasis will be on intuition and practical examples rather than theoretical results, though some experience with probability, statistics, and linear algebra will be important.

Student Learning Outcomes

• Direct their own learning in new and emerging machine learning tools and approaches by navigating API documentation and engaging in experimentation.
• Demonstrate a familiarity with a wide range of concepts in the field of machine learning and neural networks in particular.
• Demonstrate proficiency with existing coding languages (e.g., Python), packages related to machine learning (numpy, matplotlib, scikit-learn, and tensorflow), and the application of appropriate machine learning approaches for data science problems and questions.
• Evaluate and implement simple machine learning solutions used in the context of security.
• Understand and apply the concepts of machine learning using techniques and tools common in industry.

Previously listed as CYBER W207. Before Fall 2025, this course was titled “Applied Machine Learning for Cybersecurity.”