Computer Science (MSCS)
The Master of Science in Computer Science, also referred as the MSCS, will help students become an expert in theoretical and practical knowledge of computer science. This program will prepare students for a variety of fields in computer science including cybersecurity, machine learning, networking, software engineering, operating systems, computer architecture, programming, and research methodologies for publications.
Along with developing a strong foundation in computer science, our program provides a unique opportunity for those interested in moving into management roles to gain knowledge and skills focused on technology leadership.
Quick Facts
- Full-time students can complete the program in one year
- Fall, spring, and summer semester: students can start in any semester
- A minimum of 30 credit hours is required to complete the program
- Concentrations in cyber operations and machine learning
- Classes are primarily face-to-face on the Dahlonega campus, with some offered in online or hybrid modalities
- A thesis option is available with a faculty advisor for students with an interest in academic research
- Courses offered on the Dahlonega campus
- The program is face-to-face; however, some online or hybrid courses may be offered
- Students can use courses that are part of this Master of Science in Computer Science program to complete graduate certificates in cybersecurity and/or technology leadership
Program Application Deadlines
All application materials are to be received prior to the deadline. If program capacity is met prior to established admission deadlines, we will stop accepting applications for admission and cancel remaining incomplete applicants. We encourage you to apply early.
Spring application deadline - November 1
Fall application deadline - May 1
Fall Deadline
- July 15
Spring Deadline
- December 1
Summer Deadline
- April 15
How to Apply to 正澳门六合彩开奖结果's MSCS
Learn More About Our Program
The program may be completed in one year for full-time students. Interested students may elect to complete graduate certificates in cybersecurity and/or technology leadership by using some courses that are part of this Master of Science in Computer Science program, which can be very useful in preparing to the workforce.
The Cottrell Center for Business, Technology & Innovation provides three specialized labs for use in teaching some classes in this program giving you hand-on experiences for student research projects. The labs are: Cyber Range, Cyber and Forensics Lab, and Hardware and Networking Lab.
You will have the option to complete a thesis while conducting research with a faculty advisor. This research focus will prepare students both for jobs in the industry and to enter a Ph.D. program. You may also choose to do a project related to your focus in the field.
- Add a concentration in cyber operations or machine learning if you choose to
- Work in three specialized labs designed for collaborative work on student research projects
- Engage in faculty-designed coursework to help the students develop their communication, leadership, negotiation, and team management abilities
- Work with industry employees on projects that will make you more competitive in the job market
About the MSCS Curriculum
Core Requirements
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The course focuses on advanced OS concepts such as: memory and process management for high-performance computing and architectures, advanced threading/concurrency, and distributed architectures, performance enhancing techniques, memory hierarchy (including cache memory), pipelining, multiprocessor architectures, and implications to operating system design. The course emphasizes performance modeling with simulation and reading papers on the various advanced topics of operating systems. Discussion of grid computing and cloud computing, virtualization and hypervisors, scheduling for real-time, symmetric multiprocessing and hardware multithreading, effects and control of hardware caches.
Hours:
3
-
This course is an advanced computer forensics, focusing on Windows systems. The course focuses on advanced file system analysis, web and email, registry, as well as a comprehensive final case involving a moot court exercise. It will utilize existing open source tools.
Prerequisite/Corequisite:
Prerequisite: Departmental Approval
Hours:
3
-
This course sits the intersection of computer security and software engineering. It provides students with a foundation of secure software development by applying security principles to software engineering lifecycle. Students will learn practical secure software developing and testing skills.
Hours:
3
-
This course will provide a survey and in-depth discussion on selective topics of network security. It will bring together thoroughly updated coverage of all basic concepts, terminology, and issues, along with the practical skills essential to network security. Core topics include up-to-date discussion of encryption fundamentals, digital signature and certificate, network/wireless network/virtual private network security and applications, practical applications of firewalls, security policies and security standards.
Hours:
3
-
This course covers the-state-of-the-art machine learning techniques. Focuses will be put on deep learning, kernel methods and ensemble learning. Students will learn applying advanced machine learning techniques to solve challenging problems, especially big data problems. The class will cover topics in regression, classification, mixture models, neural networks, introduction of deep learning, ensemble methods and reinforcement learning.
Hours:
3
-
This course is an introduction to deep learning, a branch of machine learning concerned with the development and application of modern neural networks. Deep learning algorithms extract layered high-level representations of data in a way that maximizes performance on a given task such as facial recognition, speech recognition, and self-driven cars.聽 Deep learning enables advanced AI applications. Range of topics will be presented in this course from basic neural networks, convolutional and recurrent network structures, deep unsupervised and reinforcement learning, and applications to problem domains like speech recognition and computer vision.
Hours:
3
-
This course provides advanced concepts of business intelligence (BI) as components and functionality of information systems. It explores how business problems can be solved effectively by using operational data to create data warehouses, and then applying data mining tools and analytics to gain new insights into organizational operations. Detailed discussion of the analysis, design and implementation of systems for BI, including: the differences between types of reporting and analytics, enterprise data warehousing, data management systems, decision support systems, knowledge management systems, big data and data/text mining.聽 Case studies are used to explore the use of application software, web tools, success and limitations of BI as well as technical and social issues.
Hours:
3
-
This course provides an insight into the art and science of software reverse-engineering. It covers topics on how to approach complex problems of analyzing malicious code for the purpose of understanding its internals. By learning the techniques of reverse-engineering, students will observe how a seemingly insurmountable problem of malware binary analysis gradually breaks down into tractable components that can be easily studied, interpreted, and documented. The anatomy, behavior and manifestation of malware will be discussed. Students will receive hands-on experience with techniques analyzing, disassembling, debugging and monitoring malware in a controlled environment.
Hours:
3
Electives
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This course is designed to help students understand the critical role of cybersecurity in business and society today. The technical content of the course provides a broad overview of essential concepts and methods for assessing and assuring security in information systems and networks. In addition, the course examines the importance of security policy and management, information security as it relates to business risk and compliance, social issues such as individual privacy, and the role of public policy and international law.
Hours:
1
-
This is a graduate-level course in applied computer security and cryptography. Topics include software vulnerability analysis, defense, and exploitation, reverse engineering, and applied cryptography. Students will also learn to develop security policy and design secure critical systems.
Hours:
3
-
Project management is a preferred methodology to plan and execute IT projects. This course covers principles to manage projects at the individual level, but more so on building and maintaining project infrastructure at the aggregate level. Learning objectives are germane to leadership of information technology departments or divisions.
Hours:
3
-
This course emphasizes strategic and structural aspects of technology-related operations. It emphasizes the CIO-level perspective and enables students to comprehend the complexity of data-driven enterprises. It prepares students to navigate complex systems and environments and effectively develop capabilities for achieving competitive digital advantage.
Hours:
4
-
Students interested in academic research (and perhaps continuing to acquire a Doctorate) are encouraged to pursue the degree via the thesis option curriculum.聽 Students are required to complete experimental and/or theoretical investigation of a relevant topic in computer science that can lead to a quality publication. A written thesis must be defended and approved by the assigned research faculty members.
Hours:
6
Add On a Graduate Certificate
You may elect to apply and complete a graduate certificate in cybersecurity and/or technology leadership using these courses as electives in the Master of Science in Computer Science program.
Questions?
Carolyn.Pelkey@ung.edu