COMP-4733 Details
COMP 4733 Artificial Intelligence for Cybersecurity
Course description
This course provides an accessible introduction to artificial intelligence and machine learning with a focus on applications in cybersecurity. Designed for students with a wide range of backgrounds, including those with little to no prior experience in AI, the course emphasizes practical skills and real-world relevance. Over a 10-week period, students learn foundational AI and ML concepts and apply them to contemporary cybersecurity challenges.
The structure of the course is heavily project-based, culminating in a substantial final project completed individually or in groups. Throughout the term, students develop solutions to realistic security problems such as detecting malicious activity in network traffic, classifying benign versus malicious behavior, and analyzing system vulnerabilities using AI-driven techniques.
The course aims to equip students with practical, industry-aligned skills at the intersection of two rapidly evolving fields: artificial intelligence and cybersecurity. Students complete the course with hands-on experience, portfolio-ready projects, and exposure to tools and methods that reflect current trends in the cybersecurity landscape.
Course topics
- Foundations of Artificial Intelligence and Machine Learning
- History, ethics, and societal impacts of AI
- Search and optimization algorithms (DFS, BFS, A*, Minimax)
- Knowledge representation and reasoning
- Probabilistic reasoning and uncertainty modeling (Bayesian networks, Markov models)
- Reinforcement learning
- Supervised and unsupervised learning (classification, regression, clustering)
- Neural networks and deep learning
- Natural Language Processing (NLP), transformers, and Large Language Models
- AI for cybersecurity (anomaly detection, intrusion detection, adversarial attacks)
- Data science for threat intelligence
- Digital forensics and AI applications
- Secure and ethical AI deployment
Prerequisites
COMP-4006