Master of Science in Computer Science

Overview
Program Requirements

The Master of Science in Computer Science program is designed to equip students with advanced knowledge and skills to address complex computing challenges. Students synthesize and evaluate difficult problems using computer science theory, interdisciplinary methods, and engineering principles to develop innovative computing solutions.

The program emphasizes software engineering, data science, artificial intelligence, and machine learning—preparing graduates to design and evaluate scalable, secure, and sustainable computer systems. Students gain proficiency in programming languages, algorithms, and data structures, while learning to apply advanced computing principles to real-world applications across industries.

Strong communication and collaboration are central to this computer science program. Students refine their ability to explain technical concepts to diverse audiences, engage in research, and uphold ethical and professional standards in computing practice. Graduates emerge ready to lead projects that leverage technology to create effective, responsible, and high-quality solutions to complex technical and societal problems.

It is recommended that students in this program have strong quantitative and analytical foundations.

Spanish language learners may complete the Computer Science program through select courses.

Degree Program Objectives

In addition to the institutional and degree level learning objectives, graduates of this program are expected to achieve these learning outcomes:

Lead the design, development, and evaluation of secure, scalable software systems and computing applications.
Apply advanced computer science principles and engineering methods to analyze and solve complex problems.
Communicate technical and research findings clearly and effectively.
Uphold ethical and legal responsibilities in computer science practice with awareness of societal impact.
Collaborate in diverse teams to deliver innovative, high-quality computing solutions for industry and academia.

Degree at a Glance

Degree at a Glance table - Master's Computer Science

Core Requirements

General Concentration

Final Program Requirement

Total Semester Hours

Degree Program Requirements

Core Requirements (12 semester hours)

Core Requirements Courses Table

CSCI500

Foundations of Advanced Computer Science

CSCI505

Advanced Algorithms and Data Structures

CSCI510

Applied Machine Learning and Artificial Intelligence

CSCI520

Big Data Analytics & Data Mining

Total Semester Hours

General Concentration (18 semester hours)

This computer science concentration equips graduate students to engineer secure, scalable, and user-focused computing systems across the full stack. Coursework integrates cybersecurity, software engineering, DevSecOps, human-computer interaction, cloud computing, computer architecture, and operating systems. Students gain hands-on experience with network security, data science, and automation techniques to design reliable and defensible systems.

Through applied projects, students learn to implement machine learning for anomaly detection, design cloud-native applications, and optimize performance from hardware through runtime environments. Emphasis is placed on formal methods, measurement-based validation, and alignment with recognized security frameworks.

Graduates will be prepared for careers in secure software engineering, cloud architecture, cybersecurity engineering, UX engineering, and systems development, with the ability to integrate advanced computing concepts into practical, scalable, and human-centered technology solutions.

Objectives

Upon successful completion of this concentration, the student will be able to:

Design, secure, and optimize cloud-native systems using cybersecurity and network defense strategies.
Apply DevSecOps and automation principles to enhance reliability and scalability.
Evaluate usability and human-computer interaction (HCI/UX) through empirical research.
Integrate machine learning and data-driven approaches for threat-informed decision-making.
Employ computer architecture and operating systems knowledge to improve system performance and security.