Complete all courses and requirements listed below unless otherwise indicated.

Students should refer to the course numbering table for graduate course leveling.

Align Bridge Coursework 

Students are required to take all bridge courses unless otherwise determined by the program.

A grade of B or higher is required in each course.

Fundamentals
CS 5001
and CS 5003
Intensive Foundations of Computer Science
and Recitation for CS 5001
4
Discrete Structures
CS 5002Discrete Structures4
Object-Oriented Design
CS 5004
and CS 5005
Object-Oriented Design
and Recitation for CS 5004
4
Additional Align Courses
CS 5008
and CS 5009
Data Structures, Algorithms, and Their Applications within Computer Systems
and Recitation for CS 5008
4

Core Requirements

CS 5800Algorithms4

Breadth Areas

Complete three courses from two of the following breath areas:12
Artificial Intelligence and Data Science
Foundations of Artificial Intelligence
Game Artificial Intelligence
Database Management Systems
Pattern Recognition and Computer Vision
Natural Language Processing
Machine Learning
Information Retrieval
Data Mining Techniques
Large-Scale Parallel Data Processing
Advanced Machine Learning
Systems and Software
Principles of Programming Language
Foundations of Software Engineering
Mobile Application Development
Computer Systems
Web Development
Fundamentals of Computer Networking
Building Game Engines
Compilers
Advanced Software Development
Fundamentals of Cloud Computing
Building Scalable Distributed Systems
Theory and Security
Privacy, Security, and Usability
Complexity Theory
Software Vulnerabilities and Security
Network Security

Electives

Complete 12 semester hours from the breadth area courses and/or the following:12
Mixed Reality
Artificial Intelligence for Human-Computer Interaction
Reinforcement Learning and Sequential Decision Making
Computer Graphics
Robotic Science and Systems
Computer/Human Interaction
Computational Geometry
Noninteractive Computer Graphics
Game Programming
Advanced Computer Science Topics for Teachers
Introduction to Inclusive Computer Science Teaching
Topics
Projects for Professionals
Engaging with Industry Partners for Rising Professionals
Directed Study
Natural Language Processing
Empirical Research Methods
Operating Systems Implementation
Co-op Work Experience - Half-Time
Co-op Work Experience Abroad - Half-Time
Co-op Work Experience
Co-op Work Experience Abroad
Practicum
Topics in Computer Science
Deep Learning
Seminar in Artificial Intelligence
Special Topics in Artificial Intelligence
Statistical Methods for Computer Science
Principles of Scalable Data Management: Theory, Algorithms, and Database Systems
Information Visualization: Theory and Applications
Visualization for Network Science
Seminar in Database Systems
Special Topics in Data Science
Special Topics in Data Visualization
Empirical Research Methods for Human Computer Interaction
Machine Learning with Graphs
Theory and Methods in Human Computer Interaction
Seminar in Human-Computer Interaction
Special Topics in Graphics/Image Processing
Special Topics in Human-Centered Computing
Intensive Principles of Programming Languages
Formal Specification, Verification, and Synthesis
Seminar in Programming Languages
Special Topics in Programming Language
Special Topics in Formal Methods
Seminar in Software Engineering
Special Topics in Software Engineering
Intensive Computer Systems
Foundations of Distributed Systems
Seminar in Computer Systems
Master's Research
Special Topics in Computer Systems
Seminar in Computer Networks
Seminar in Computer Security
Advanced Algorithms
Foundations of Cryptography
Foundations and Applications of Information Theory
Seminar in Theoretical Computer Science
Special Topics in Theoretical Computer Science
Effective Scientific Writing in Computer Science
Research Capstone
Thesis
Master’s Project
Readings
Cybersecurity: Technologies, Threats, and Defenses
Cybersecurity Principles and Practices
Computer System Security
Information System Forensics
Software Security Practices
Essentials of Data Science
Unsupervised Machine Learning and Data Mining

Program Credit/GPA Requirements

36-44 total semester hours required
Minimum 3.000 GPA required