Computer Science
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Computer Science, M.S. Overview
University of West Florida’s innovative M.S. in computer science online degree program provides you with the skills to stay competitive in the industry and be a technical leader in your organization. Blending foundational skills with modern topics in computer science and technology, you’ll explore advanced topics in algorithmic programming, parallel computing, systems and networks, artificial intelligence and data analytics.
Featuring small class sizes, our online CS degree offers the opportunity to interact and experience individualized attention with research faculty. The program’s online format gives you the opportunity to complete your studies on your schedule.
Through an innovative curriculum, you will study topics such as:
- Algorithmic programming, software development and research of computational methods
- Parallel programming and cloud and high performance computing
- Machine learning for decision support
- Efficient data processing and mining of large data sets in a Hadoop cluster computing environment
- Agile and continuous software engineering for modern software development, integration and delivery
Candidates for This Program Include:
- Students with an undergraduate degree in computer science, information technology or another closely related area
- Current computer science professionals who want to advance their career in the field
- Those seeking a deeper understanding of the field and its advanced skills
Learning Outcomes
- Demonstrate competence in solving complex computational problems
- Extract knowledge from large data sets for decision support
- Harness the power of advanced computing architecture
Courses and Requirements
UWF’s online CS degree includes a total of 30 credit hours, including 15 credit hours of core computer science topics. Customize your degree with a concentration in either software engineering or data analytics and nine credit hours of elective courses.
At a minimum, we expect students to have completed undergraduate mathematics and science courses as typically expected in an undergraduate science or engineering degree program. Students entering the program with a bachelor’s degree other than Computer Science will be required to complete prerequisite foundational courses in computing and programming. Any foundational courses needed will count toward the program’s 30 total credit hours as part of the 9 required elective credit hours.
- COP 5518 - Foundations: Computing Essentials
3 Credit Hours
Foundations: Computing Essentials
This course reviews fundamental principles of modern computer architectures, operating systems and computer networks and relates them to computer programming. The course covers topics such as the design of various components of operating systems and services they provide to users and application developers, network structures & devices, network protocol stacks, network performance metrics, network routing algorithms, and network traffic analysis. The role of security in systems and networks will also be covered. This course may require completion of graduate foundations courses in computer programming or the equivalent undergraduate coursework if a student has insufficient academic or professional experience in the discipline.
- COP 5007 - Foundations: Programming Essentials
3 Credit Hours
Foundations: Programming Essentials
A course in the Accelerated Software Engineering Foundations Series in which students will gain a comprehensive understanding of principles/concepts of Java programming and how to apply those principles/concepts in conjunction with principles of software engineering to design and develop object- oriented software systems. Students taking this course should have an understanding of programming language fundamentals including variables, constants, selection, iteration, arrays, and functions or methods.
- COP 5417 - Foundations: Data Structures & Algorithms Essentials
3 Credit Hours
Foundations: Data Structures & Algorithms Essentials
A comprehensive overview of the most commonly used data structures including arrays, linked lists, trees, graphs, hash tables, and heaps. A survey of common algorithms including those that are used with the data structures as well as sorting, searching, divide-and-conquer, greedy algorithms and dynamic programming. Students taking this course should have a good understanding of programming language fundamentals including variables, constants, selection, iteration, arrays, file I/O and functions. This course may require completion of graduate foundations courses in computer programming or the equivalent undergraduate coursework if a student has insufficient academic or professional experience in the discipline.
- COP 5518 - Foundations: Computing Essentials
- COP 5725 - Database Systems
3 Credit Hours
Database Systems
Introduction to database systems and database management system architectures. Various database models are discussed with emphasis on the relational model and relational database design. Case applications using fourth-generation languages, such as SQL are included. This course requires completion of graduate foundations courses in computer programming or the equivalent undergraduate coursework.
- COP 5522 - Parallel and Distributed Programming
3 Credit Hours
Parallel and Distributed Programming
A comprehensive overview of parallel programming using MPI and OpenMP. A survey of common parallel architectures, communication primitives, applications of those primitives to design efficient parallel algorithms, definition of models and metrics to evaluate the effectiveness of parallel algorithms theoretically and empirically, and introduction to cloud computing. Students taking this course should have a good understanding of undergraduate level data structures and algorithms, and mastery of undergraduate level programming in a UNIX environment.
- COP 6416 - Advanced Algorithms
3 Credit Hours
Advanced Algorithms
A comprehensive overview of the most commonly used approaches for approximate solution of NP-Hard problems, including linear programming, dynamic programming, and greedy algorithms. A survey of common algorithms including cache-aware algorithms, randomized algorithms, network flow algorithms, and online algorithms. This course will take an "experimental algorithms" approach to educating students on augmenting theoretical results with empirical methods for the design of algorithms that are effective in practice. Students taking this course should have a good understanding of undergraduate-level data structures and algorithms, competence in programming, and the ability to write formal proofs.
Select one to be completed over two semesters (6 credits):
- CIS 6971 - Thesis
3 Credit Hours
Thesis
Normally 3 Credit Hours in two consecutive semesters. Graded on satisfactory/unsatisfactory basis only. Permission is required.
- COT 6931 - Computer Science Project
3 Credit Hours
Computer Science Project
Capstone course for Masters students who do not elect the thesis option. Normally taken for 3 credits in each of two consecutive semesters. Students will define and carry out a project that shows mastery of some topic in computing and produces some concrete product such as a report or a computer program. Students should not enroll until they have completed at least 15 semester hours of their graduate coursework. Permission is required.
- COP 5725 - Database Systems
Select one advisor-approved concentration.
Software Engineering
- CEN 6030 - Agile Software Engineering
3 Credit Hours
Agile Software Engineering
Analysis and overview of concepts in agile software development. Covers agile principles, methodologies, practices, and artifacts. This course may require completion of graduate foundations courses in computer programming or the equivalent undergraduate coursework if a student has insufficient academic or professional experience in computer science. Prerequisites: COT 5405
- CEN 6017 - Continuous Software Engineering
3 Credit Hours
Continuous Software Engineering
This course focuses on aspects of modern software engineering as they pertain to continuous workflows. Topics of continuous testing, integration, delivery, and deployment will be discussed throughout the course. Significant programming experience is required for this course. Concurrent Prerequisites CEN 6080.
Data Analytics
- CAP 6771 - Data Mining
3 Credit Hours
Data Mining
The course addresses methods to discover patterns and trends in large datasets. With the aid of contemporary data mining software, students will apply the theoretical skills they acquire in the course to go through the complete data mining process starting from data pre-processing and cleaning, concept hierarchy generation, attribute relevance analysis to frequent itemset mining and association rule mining. Traditional methods such as Bayesian decision theory as well as modern approaches in classification and unsupervised clustering will be covered as well. Prerequisite: COP 5725
- CAP 6789 - Advanced Big Data Analytics
3 Credit Hours
Advanced Big Data Analytics
In this course students study advanced methods to handle and analyze very large data sets in Hadoop's Big Data environment. Students work with the Spark architecture in the MapReduce framework. Students also learn to apply machine learning algorithms in Spark.
- CEN 6030 - Agile Software Engineering
Select three:
- CAP 5600 - Introduction to Artificial Intelligence
3 Credit Hours
Introduction to Artificial Intelligence
Introduction to basic artificial intelligence theories and methods for solving complex and difficult problems using computers; goal-oriented procedures, search problems, knowledge representation and machine learning. Topics will include intelligent systems such as expert systems, intelligent agents and robots. Will be conducted within a cognitive science framework.
- CAP 6610 - Machine Learning
3 Credit Hours
Machine Learning
This course provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, decision trees, and neural network, deep learning, deep sequence modeling, deep convolutional models), unsupervised learning (clustering, dimensionality reduction, anomaly detection, and deep generative models), model evaluation (k-fold cross validation & performance evaluation metrics) and hyper-parameter tuning. The goal of the course is for the students to master the key theoretical concepts and gain the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems via hands-on projects.
- CAP 6665 - Computer Vision
3 Credit Hours
Computer Vision
This course introduces and demonstrates the applications and algorithms in Computer Vision. The course includes fundamentals of image processing and formation, feature detection, recognition, and reconstruction. Activities and projects will be used to develop intelligent image processing algorithms. The class provides instructions and practical exercises in detection and segmentation, representation, and understanding geometric structures for computer vision applications. The class will focus on mathematical and theoretical foundations of computer vision methods.
- CIS 6415 - Advanced Computer Systems and Networks
3 Credit Hours
Advanced Computer Systems and Networks
Examines current advancements in computer hardware, operating systems and networks, their relation to each other and programming practices that takes advantage of them. Topics include pipelined, hyperthreaded, multicore and multiprocessor architectures, scheduling methods, distributed and real-time systems, high-speed networks, routing, congestion and flow control and quality of service.
- COP 6727 - Advanced Database Systems
3 Credit Hours
Advanced Database Systems
Advanced topics in database management systems will be covered, for example: further dependencies and higher normal forms, transaction processing, concurrency control, backup and recovery, indexing, replication, managing large databases and contemporary issues and topics in databases. Prerequisite: COP 5725.
5000/6000 level advisor-approved elective
- CAP 5600 - Introduction to Artificial Intelligence
Admission Requirements
To be considered for admission into UWF’s online computer science program, you must have an undergraduate degree from an accredited institution, with a minimum institutional GPA of 3.0 on a 4.0 scale on the last 60 hours of coursework in the baccalaureate degree.
How to Apply
To apply for admission to this program, you first need to submit an application for graduate admission (plus a $30 application fee) and be accepted for admission into University of West Florida. In addition, you must:
- Submit official transcripts confirming a bachelor’s degree from an institution whose accrediting agency is included on the list of UWF approved accrediting agencies
- Submit a letter of intent describing your work experience in the field and reasons for pursuing the degree, including how the degree relates to your future career goals
- Submit contact information (email addresses and phone numbers) for two professional references
- Submit a resume
- Graduate Record Examination (GRE) is optional but highly recommended for international students seeking admission to the campus program
Have questions about this program or the admissions process? Connect with one of our knowledgeable enrollment counselors.
Costs & Financial Aid
| Component | Cost | Total* |
|---|---|---|
| Full Online Program Tuition | $425 per credit hour | $12,750.00 |
| Tuition with Maximum Transfer Credits (Up to 6) | $425 per credit hour | $10,200.00 |
| Full Face-to-Face In-State Program Tuition | $377.60 per credit hour | $11,328.00 |
Time to completion varies by student, depending on individual progress and credits transferred, if applicable. Fees are charged per semester unless otherwise noted. This program takes up to six semesters to complete, depending on transfer credits. For a personalized estimate of time to completion, call an enrollment advisor at 844.372.9390 or request information.
Refer to UWF Cost of Attendance Estimates and Financial Literacy for more information on UWF costs and financial aid.
* Tuition and fees are subject to change.
Military Students
UWF proudly serves active duty U.S. military members and veterans. As UWF has been a participant of the Yellow Ribbon Program since 2011, you could be eligible to receive free tuition with your military benefits.
See How We Can Serve YouFinancial Aid
Funding your college education should not empty your wallet. We offer various financial aid options for our online students, including loans, scholarships and grants for degree-seeking students.
Learn More About Financial AidCareer Outcomes
Upon completion of our online CS degree, you can pursue a variety of careers within the field.
* Salary and job outlook information from the Bureau of Labor Statistics.
Computer and Information Research Scientists
Computer and information research scientists are responsible for developing new computing technology concepts and discovering innovative uses for current technology. The median annual salary for the position is $131,490, and employment is projected to grow 19 percent through 2031.
Computer Systems Analysts
In charge of assessing computer systems and procedures, computer systems analysts determine and implement solutions to maximize an organization’s efficiency. Computer systems analysts earn a median salary of $99,270 per year, and employment is projected to increase 9 percent through 2031.
Software Engineers
Software engineers design and develop programs that meet user needs for use on computers and other devices. They also conduct software maintenance after their product has launched or integrate new software with existing software systems. The median annual salary for software developers is $109,020, and employment is expected to grow 25 percent through 2031.