Software Engineering Systems, MS (Arlington)

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The software engineering systems program takes a sociotechnical, engineering approach to software. This engineering foundation is designed to enable students to embrace real-world complexity as a golden opportunity, especially for the more technically advanced student. We are committed to shaping our students to be intuitive problem solvers, experienced engineering architects, and result leaders who will have a great impact at the exciting three-way intersection of computer science, engineering, and ethics.

Our program offers a multitude of courses in Big Data engineering and analytics, in addition to supplementary courses that are required to deliver the data analytics results in a meaningful way to management. We cover data management, advanced data management, business intelligence, column databases, data science, and Big Data engineering. We offer advanced functional programming using the powerful Scala language and a course on advanced data science as well as cloud computing. Multithread concurrent computing is also offered as it is important for synchronizing a huge set of servers working in parallel to do large-scale analytics to make things run faster by a hundredfold increase in speed. Due to the high-level mathematical operations required to run these programs, only software engineers have the capacity to work in such complicated areas. Only they can make the necessary mathematical algorithms execute quickly enough to get the finest results.

Our engineers become fluent in data science for the sake of building the actual system. They study how to write machine-learning algorithms on top of statistical packages.

• Students study the fundamentals of logical computing formulation and program construction as well as the mathematical modeling and analysis of algorithms—an essential aspect of data science analytics.
• Students study clustering techniques, along with topic modeling and classification and logical regression techniques, as well as Bayesian statistics.
• Students study how to configure and operate a Hadoop environment (large clusters of commodity hardware) and in the process how to integrate data from diverse sources to move and manage data through Big Data platforms (in-house or in the cloud). Data ingestion, the filtering and firing of millions of operations to run over large clusters of commodity hardware, is a software engineering technique that we teach our students how to perform through Scala, multithreading, Spark programming, and “map-reduce” techniques.
• We show students how to make the business case for analytics projects and how to follow an execution road map that involves understanding the architectures underpinning such gigantic platforms as well as the resourcing and cost issues.

Degree Requirements

Students in the program must complete 32 semester hours of approved coursework with a minimum grade-point average of 3.000. Students can complete a master's degree by pursuing any of one of the three options: coursework, project, or thesis. 

Master's project and thesis options must be carried out under the supervision of a professor and must have prior approval of the program director. 

Beginning with students admitted in the fall of 2026, all students pursuing on-ground master's degree programs must complete a university-level experiential learning requirement. This requirement may be fulfilled through the curriculum, co-op, or other work- or industry-integrated learning experiences.

Complete all courses and requirements listed below unless otherwise indicated.

Core Requirements

Course List

Code	Title	Hours
The College of Engineering requires that students must earn a grade of C or higher in all required core courses to fulfill degree requirements. Prerequisite conditions of individual core courses may require a higher minimum grade.
CSYE 6200	Concepts of Object-Oriented Design	4
CSYE 7230	Software Engineering	4
INFO 6205	Program Structure and Algorithms	4

Options

Complete one of the following options:

Coursework Option

Course List

Code	Title	Hours
Complete 8 semester hours from the restricted electives course list below.		8
Complete 12 semester hours from the other electives course list below.		12

Project Option

Course List

Code	Title	Hours
CSYE 7945	Master's Project	4
Complete 4 semester hours from the restricted electives course list below.		4
Complete 12 semester hours from the other electives course list below.		12

Thesis Option 

Course List

Code	Title	Hours
CSYE 7945	Master's Project	4
CSYE 7990	Thesis	4
Complete 12 semester hours from the other electives course list below.		12
In addition to completing the thesis course, students must successfully complete the thesis submission process, including securing committee and Graduate School of Engineering signatures and submission of an electronic copy of their MS thesis to ProQuest.

Restricted Electives

Course List

Code	Title	Hours
Complete restricted elective requirements from the following subject code:
CSYE

Other Electives

Course List

Code	Title	Hours
Complete the remaining minimum program required semester hours from the following subject codes:
CSYE
DAMG
INFO (INFO 6250 excluded)
TELE

Optional Co-op Experience

Course List

Code	Title	Hours
Complete the following (students must complete ENCP 6000 to qualify for co-op experience):
ENCP 6000	Career Management for Engineers	1
ENCP 6964	Co-op Work Experience	0
or ENCP 6954	Co-op Work Experience - Half-Time
or ENCP 6955	Co-op Work Experience Abroad - Half-Time
or ENCP 6965	Co-op Work Experience Abroad

Program Credit/GPA Requirements

32 total semester hours required (33 with optional co-op)
Minimum 3.000 GPA required