Online M.S.

in Computer Science

Expand your career opportunities with an online master’s degree in computer science.

Academics

Online Options
Academic Program
Courses

The online M.S. in Computer Science is a flexible, fully online master’s program for busy professionals who want to solve big problems through computing. The program combines the academic rigor and high quality of our top-ranked in-person degree with the flexibility of an online program, allowing students to fit classes into their busy schedules.

Online Options

100% online

All courses are fully online, and many can be completed asynchronously. Most courses include opportunities for synchronous interaction with faculty.

Begin online, finish in-person

Jumpstart your degree by taking four courses online, then come to campus for face-to-face courses and an in-person campus experience. This hybrid option may be of interest to international students seeking internships and other experiential learning opportunities in the United States.

Try a class

Take up to two online courses before applying to our program. If you later join the program, you can transfer the credits earned towards your degree. Learn how »

Academic Program

The online M.S. in Computer Science has the same degree requirements as the in-person program:

Four core requirements (at least one from each of these three areas: theory, systems, artificial intelligence)
A total of 30 credits in graduate-level computer science or related fields
Must include 12 credits in 600-level classes

See the Course Requirements page for details.

Courses

The online M.S. in Computer Science is designed to take two and a half to four years to complete, depending on how many courses you take per semester. New online courses will be added every year to ensure that students have access to our most popular master's level courses and can complete their degree requirements. The course schedule is subject to change.

Asynchronous course lectures will be recorded and available on-demand. Synchronous course lectures will be held at designated times.

spring 2023

COMPSCI 532 Systems for Data Science

In this course, students will learn the fundamentals behind large-scale systems in the context of data science. We will cover the issues involved in scaling up (to many processors) and out (to many nodes) parallelism in order to perform fast analyses on large datasets. These include locality and data representation, concurrency, distributed databases and systems, performance analysis and understanding. We will explore the details of existing and emerging data science platforms, including MapReduce-Hadoop, Spark, and more. This course counts as an Elective toward the CS Major.

COMPSCI 561 System Defense and Test

This class trains students to detect and analyze weaknesses and vulnerabilities in target systems as a method of assessing the security of a system. We focus on tools and techniques that an attacker would employ but from the perspective of an ethical system administrator. Topics include tools and techniques for penetration testing and attacks, information gathering, social engineering, and defenses. Specific topics include malware, denial of service attacks, SQL injection, buffer overflow, session hijacking, and system hacking, network sniffing and scans, wireless encryption weaknesses and other WiFi issues, IDS/firewall evasion, metasploit tools, physical security, and setting up honeypots. Was INFOSEC 690S. This course counts as an Elective toward the CS Major.

COMPSCI 590J Cyber Effects: Reverse Engineering, Exploit Analysis, and Capbility Development

This course covers a broad range of topics related to cyber security and operations. Our focus is on real world studies of reverse engineering, exploit analysis, and capability development within the context of computer network operations and attack. The course has an emphasis on hands-on exercises and projects. Topics covered include computer architecture and assembly language, principles of embedded security, the essentials of exploit development and analysis (including using industry standard tools such as Ghidra, and utilizing computer security databases such as CVE), and discussion of real-world events and techniques. This course counts as an Elective toward the CS Major.

COMPSCI 590K Advanced Digital Forensic Systems

This course introduces students to the principal activities and state-of-the-art techniques involved in developing digital forensics systems. Topics covered may include: advanced file carving and reconstruction, forensic analysis of modern filesystems, network forensics, mobile device forensics, memory forensics, and anti-forensics. This course counts as an Elective toward the CS Major.

COMPSCI 677 Distributed and Operating Systems

An in-depth examination of principles of distributed systems and advanced operating systems. Topics include client-server programming, distributed scheduling, virtualization and cloud computing, distributed storage, IoT. Familiarity with an undergraduate course on operating systems (COMPSCI 377 or equivalent) is helpful.