Not available at this time

Not available at this time

The course provides an introduction to machine learning algorithms and applications, and is intended for students with no prior experience with machine learning. Machine learning algorithms answer the question: 'How can a computer improve its performance based on data and from its own experience?' The course is roughly divided into thirds: supervised learning (learning from labeled data), reinforcement learning (learning via trial and error), and real-world considerations like ethics, safety, and fairness.

The course explores key concepts of artificial intelligence, including state-space and heuristic search techniques, game playing, knowledge representation, automated planning, reasoning under uncertainty, decision theory and machine learning. We will examine how these concepts are applied in the context of several applications.

The design and operation of modern computer operating systems. Review of capabilities of typical computer hardware. Topics include command language interpreter (the shell), processes, concurrency, inter-process communication, linking and loading, memory management, transactions, file systems, distributed systems, security, and protection. Programming projects in C.

The design and operation of modern computer operating systems. Review of capabilities of typical computer hardware. Topics include command language interpreter (the shell), processes, concurrency, inter-process communication, linking and loading, memory management, transactions, file systems, distributed systems, security, and protection. Programming projects in C.

Many software developers aren't aware of how to properly write secure code. This course covers practical skills in reverse engineering and binary exploitation, and examines the techniques used by hackers in recent major security incidents. The course objective is to provide students with a strong understanding of attack patterns, and to ensure students implement more secure coding practices in their own code. This course begins with an introduction to Intel-based assembly, reverse engineering, vulnerability analysis, and various forms of Linux-focused binary exploitation.

This course offers a broad introduction to the forensic investigation of digital devices. We cover the preservation, recovery, harvesting, and courtroom presentation of information from file systems, operating systems, networks, and media files. The primary goal of the class is to understand why and from where information is recoverable in these systems. We also cover relevant issues from law, privacy, and current events.

A study, analysis, and discussion of the legal issues related to crimes involving computers and networks, including topical actions by dissidents and governments. We will also study the technologies of forensic investigation, intelligence gathering, privacy enhancement, and censorship resistance. Our main legal topics will include recent and important case law, statutes, and constitutional clauses concerning authorization, access, search and seizure, wiretaps, the right to privacy, and FISA.

This course provides an introduction to the principles and practice of computer and network security. A focus on both fundamentals and practical information will be stressed. The three key topics of this course are cryptography, privacy, and network security. Subtopics include ciphers, hashes, key exchange, security services (integrity, availability, confidentiality, etc.), security attacks, vulnerabilities, anonymous communications, and countermeasures.