Data Science - M.S.

The Data Science M.S. program provides you with the theoretical knowledge and practical experience needed to succeed in today's data-driven world. With hands-on learning opportunities, experienced faculty and cutting-edge technology, you will be prepared to solve complex data challenges and make an impact in your field.

Contact Us

Apply Now
Request Information
Schedule a Visit
Find All Majors

Program Information for Data Science - M.S.

Program Description

Program Description

Full Description

The Master of Science degree in Data Science provides a focus on developing scientists who will understand the theories, methods and tools of data science and apply data science to solving research and workplace questions in the natural, health and social sciences for businesses and industries.

Data science is a STEM discipline founded on the principles of mathematics and the sciences and developed through a synthesis of mathematics and computer science. One may think of data science as a blending together of methods and ideas from analysis, statistics, databases, big data, artificial intelligence, numerical analysis, graph theory and visualization for the purposes of finding information in data and applying that information to solving real-world problems.

Admissions for Data Science - M.S.

Admissions

For more information about graduate admissions, visit the graduate admission website. For more information on international admissions, visit the international admission website.

Admission Requirements

  • Bachelor’s degree from an accredited college or university
  • Minimum 3.000 undergraduate GPA on a 4.000-point scale
  • Prerequisite mathematics and computer science courses1
  • Official transcript(s)
  • GRE scores
  • Two letters of recommendation
  • English language proficiency - all international students must provide proof of English language proficiency (unless they meet specific exceptions to waive) by earning one of the following:2
    • Minimum 71 TOEFL iBT score
    • Minimum 6.0 IELTS score
    • Minimum 50 PTE score
    • Minimum 100 DET score
1

Students entering the program are expected to have previously completed courses in linear algebra (equivalent to MATH 21001 or MATH 21002), statistics (equivalent to MATH 20011), advanced calculus (equivalent to MATH 22005), discrete mathematics/structures (equivalent to MATH 31011 or CS 23022), programming and data structures (equivalent to CS 23001) and database systems (equivalent to CS 33007). Applicants have not completed all the prerequisite courses may be admitted conditionally (based on a holistic review of their application) until they complete the remaining courses being before beginning the program’s coursework.

2

International applicants who do not meet the above test scores may be considered for conditional admission.

Application Deadlines

  • Fall Semester
    • Application deadline: June 15
  • Spring Semester
    • Application deadline: November 1
  • Summer Term
    • Application deadline: April 1

All application materials (including applicable fee, transcripts, recommendation letters, etc.) submitted after these deadlines will be considered on a space-available basis.

Learning Outcomes

Learning Outcomes

Program Learning Outcomes

Graduates of this program will be able to:

  1. Ask the questions so that problems in a particular business or industrial situation become clear.
  2. Determine if the problem may be addressed with data science methods and tools, and if yes, propose potential methods for solving the problems.
  3. Make suggestions for how data science may be used to enhance the quality and value of currently existing products (whether the products are physical or methods) and how data science may be used in the development of new products.

Coursework

On This Page

Program Requirements

Major Requirements

Major Requirements
CS 63005ADVANCED DATABASE SYSTEMS DESIGN 3
CS 63015DATA MINING TECHNIQUES 3
CS 63016BIG DATA ANALYTICS 3
MATH 50015APPLIED STATISTICS 3
MATH 50024COMPUTATIONAL STATISTICS 3
MATH 50028STATISTICAL LEARNING 3
Major Electives, choose from the following: 16
BSCI 60104
BIOLOGICAL STATISTICS
CS 54201
ARTIFICIAL INTELLIGENCE
CS 57206
DATA SECURITY AND PRIVACY
CS 63017
BIG DATA MANAGEMENT
CS 63018
PROBABILISTIC DATA MANAGEMENT
CS 63100
COMPUTATIONAL HEALTH INFORMATICS
CS 64201
ADVANCED ARTIFICIAL INTELLIGENCE
CS 64402
MULTIMEDIA SYSTEMS AND BIOMETRICS
CS 67302
INFORMATION VISUALIZATION
CS 69098
RESEARCH
or MATH 67098
 RESEARCH
ECON 62054
ECONOMETRICS I
ECON 62055
ECONOMETRICS II
ECON 62056
TIME SERIES ANALYSIS
EHS 62018
ENVIRONMENTAL HEALTH CONCEPTS IN PUBLIC HEALTH
EPI 62017
FUNDAMENTALS OF PUBLIC HEALTH EPIDEMIOLOGY
EPI 63016
PRINCIPLES OF EPIDEMIOLOGIC RESEARCH
EPI 63019
EXPERIMENTAL DESIGNS FOR CLINICAL RESEARCH
GEOG 59070
GEOGRAPHIC INFORMATION SCIENCE
GEOG 59080
ADVANCED GEOGRAPHIC INFORMATION SCIENCE
HI 60401
HEALTH INFORMATICS MANAGEMENT
HI 60411
CLINICAL ANALYTICS
HI 60414
HUMAN FACTORS AND USABILITY IN HEALTH INFORMATICS
HI 60418
CLINICAL ANALYTICS II
KM 60301
FOUNDATIONAL PRINCIPLES OF KNOWLEDGE MANAGEMENT
LIS 60020
INFORMATION ORGANIZATION
MATH 50011
PROBABILITY THEORY AND APPLICATIONS
MATH 50051
TOPICS IN PROBABILITY THEORY AND STOCHASTIC PROCESSES
MATH 50059
STOCHASTIC ACTUARIAL MODELS
PSYC 61651
QUANTITATIVE STATISTICAL ANALYSIS I
PSYC 61654
QUANTITATIVE STATISTICAL ANALYSIS II
Culminating Requirement
Choose from the following:6
Thesis Option
DATA 69199
THESIS I
Project and Internship Option
DATA 69099
CAPSTONE PROJECT
DATA 69192
GRADUATE INTERNSHIP
Project and Course Option
DATA 69099
CAPSTONE PROJECT
Approved Graduate course (50000 level or higher)
Minimum Total Credit Hours:30
1

With graduate coordinator approval, students may substitute a relevant graduate-level course (50000 or 60000 level) in either Computer Science (CS) or Mathematics (MATH).

Graduation Requirements
Minimum Major GPA Minimum Overall GPA
- 3.000
  • No more than one-half of a graduate student’s coursework may be taken in 50000-level courses.
  • Grades below C are not counted toward completion of requirements for the degree.

Culminating Experience

The culminating experience requirement is a master’s thesis or an integrated learning experience.

The master’s thesis requires a written thesis, a public defense of the thesis and approval by the student’s supervisory committee. Students must form a master's thesis committee, which will include the advisor and at least two other graduate faculty members. The thesis topic and committee must be approved by the advisor and graduate coordinator. The final version of the thesis must be approved by the advisor, thesis committee and graduate coordinator.

The integrated learning experience may include a substantial capstone project or a capstone project and internship. Students must prepare a written document explaining and/or demonstrating their capstone project or internship activity and its significance. In addition, students must give a public presentation of their capstone project or internship, and the written document and presentation must be approved by their supervisory committee.

Roadmap

Roadmap

Roadmap

This roadmap is a recommended semester-by-semester plan of study for this program. Students will work with their advisor to develop a sequence based on their academic goals and history. Courses designated as critical (!) must be completed in the semester listed to ensure a timely graduation.

Plan of Study Grid
Semester OneCredits
CS 63005 ADVANCED DATABASE SYSTEMS DESIGN 3
MATH 50015 APPLIED STATISTICS 3
Major Elective 3
 Credit Hours9
Semester Two
CS 63015 DATA MINING TECHNIQUES 3
MATH 50024 COMPUTATIONAL STATISTICS 3
MATH 50028 STATISTICAL LEARNING 3
 Credit Hours9
Semester Three
CS 63016 BIG DATA ANALYTICS 3
Major Elective 3
Culminating Requirement 3
 Credit Hours9
Semester Four
Culminating Requirement 3
 Credit Hours3
 Minimum Total Credit Hours:30

Program Delivery

Program Delivery

  • Delivery:
    • In person
  • Location:
    • Kent Campus

Examples of Possible Careers and Salaries for Data Science - M.S.

Data scientists and mathematical science occupations, all other

30.9%

much faster than the average

33,200

number of jobs

$98,230

potential earnings

Computer and information research scientists

15.4%

much faster than the average

32,700

number of jobs

$126,830

potential earnings

Statisticians

34.6%

much faster than the average

42,700

number of jobs

$92,270

potential earnings

Computer and information systems managers

10.4%

much faster than the average

461,000

number of jobs

$151,150

potential earnings

Management analysts

10.7%

much faster than the average

876,300

number of jobs

$87,660

potential earnings

Database administrators and architects

9.7%

much faster than the average

132,500

number of jobs

$98,860

potential earnings

Computer programmers

-9.4%

decline

213,900

number of jobs

$89,190

potential earnings

Software developers and software quality assurance analysts and testers

21.5%

much faster than the average

1,469,200

number of jobs

$110,140

potential earnings

Notice: Career Information Source
* Source of occupation titles and labor data comes from the U.S. Bureau of Labor Statistics' Occupational Outlook Handbook. Data comprises projected percent change in employment over the next 10 years; nation-wide employment numbers; and the yearly median wage at which half of the workers in the occupation earned more than that amount and half earned less.

Artificial Intelligence - M.S.

The Master of Science in Artificial Intelligence program provides rigorous training in the theory and application of AI, equipping you with the skills to develop intelligent systems that can solve complex problems in a variety of fields. With access to state-of-the-art technology and experienced faculty, you will gain the knowledge and practical experience needed to make an impact in this rapidly growing field.

Contact Us

Apply Now
Request Information
Schedule a Visit
Find All Majors

Program Information for Artificial Intelligence - M.S.

Program Description

Program Description

Full Description

The Master of Science degree in Artificial Intelligence prepares students with a focused educational and research environment to develop career paths through necessary learning and training with emerging artificial intelligence technologies and applications to intelligent analytics, smart homes and communities and robotics and automation. Graduates have technical knowledge and research and development skills necessary for applying artificial intelligence to industry, community and military. These areas include sectors requiring intelligent pattern-analysis of big data such as retail, healthcare, biology, psychology and intelligent human-machine interactions and interfaces.

Admissions for Artificial Intelligence - M.S.

Admissions

For more information about graduate admissions, visit the graduate admission website. For more information on international admissions, visit the international admission website.

Admission Requirements

  • Bachelor's degree from an accredited college or university
  • Minimum 3.000 undergraduate GPA on a 4.000-point scale
  • Course Proficiency: Completion of high-level algebra, geometry and calculus courses (equivalent to MATH 12002, MATH 12003, MATH 21001)1(starting with spring 2026 admissions, a minimum B grade in these courses will be required)
  • Official transcript(s)
  • GRE scores
  • Résumé
  • Goal statement
  • Two letters of recommendation
  • English language proficiency - all international students must provide proof of English language proficiency (unless they meet specific exceptions to waive) by earning one of the following:2
    • Minimum 71 TOEFL iBT score
    • Minimum 6.0 IELTS score
    • Minimum 50 PTE score
    • Minimum 100 DET score

Admission to this interdisciplinary program is holistic. Highly qualified students from related disciplines who are lacking preparation in some standard areas may be considered for admission on a case-by-case basis.

1

It is strongly recommended that applicants to the program have completed computer sciences courses with a minimum B grade in such areas as computer programming, discrete structures, data structures and abstraction, operating systems, database and computer algorithms (equivalent to CS 13011, CS 13012, CS 23001, CS 23022, CS 33007, CS 33211, CS 46101).

2

International applicants who do not meet the above test scores may be considered for conditional admission.

Application Deadlines

  • Fall Semester
    • Application deadline: June 15
  • Spring Semester
    • ​Application deadline: November 1
  • Summer Term
    • Application deadline: April 1

All application materials (including applicable fee, transcripts, recommendation letters, etc.) submitted after these deadlines will be considered on a space-available basis.

Learning Outcomes

Learning Outcomes

Program Learning Outcomes

Graduates of this program will be able to:

  1. Combine intelligent analytics and automation, human-computer interaction and robotics techniques to optimize and automate transportation, industrial processes and/or healthcare processes.
  2. Apply machine learning techniques on big data to predict, classify, data mine and explore patterns.
  3. Apply intelligent visualization and Internet-based techniques for smart homes and communities.
  4. Perform research, discovery and integration by applying knowledge of artificial intelligence theory and techniques.

Coursework

On This Page

Program Requirements

Major Requirements

Major Requirements
CS 53302ALGORITHMIC ROBOTICS 3
or CS 63018 PROBABILISTIC DATA MANAGEMENT
or CS 67302 INFORMATION VISUALIZATION
CS 54201ARTIFICIAL INTELLIGENCE 3
CS 54202MACHINE LEARNING AND DEEP LEARNING 3
CS 63005ADVANCED DATABASE SYSTEMS DESIGN 3
CS 64201ADVANCED ARTIFICIAL INTELLIGENCE 3
Major Electives, choose from the following:9
CS 53301
SOFTWARE DEVELOPMENT FOR ROBOTICS
CS 53302
ALGORITHMIC ROBOTICS
CS 53303
INTERNET OF THINGS
CS 53305
ADVANCED DIGITAL DESIGN
CS 53334
HUMAN-ROBOT INTERACTION
CS 63015
DATA MINING TECHNIQUES
CS 63016
BIG DATA ANALYTICS
CS 63017
BIG DATA MANAGEMENT
CS 63018
PROBABILISTIC DATA MANAGEMENT
CS 63100
COMPUTATIONAL HEALTH INFORMATICS
CS 63306
EMBEDDED COMPUTING
CS 64401
IMAGE PROCESSING
CS 64402
MULTIMEDIA SYSTEMS AND BIOMETRICS
CS 65203
WIRELESS AND MOBILE COMMUNICATION NETWORKS
CS 67301
SCIENTIFIC VISUALIZATION
CS 67302
INFORMATION VISUALIZATION
CS 69995
SPECIAL TOPICS IN COMPUTER SCIENCE (requires advisor approval to apply)
Culminating Requirement
Choose from the following:6
Thesis Option
CS 69199
THESIS I 1
Project Option
CS 69099
CAPSTONE PROJECT
Project Option Electives, choose from the following:
CS 69192
GRADUATE INTERNSHIP
CS 69995
SPECIAL TOPICS IN COMPUTER SCIENCE
Computer Science (CS) Graduate course (50000 or 60000 level) with advisor approval
Minimum Total Credit Hours:30
1

Students selecting the thesis option must form a master's thesis committee, which will include the advisor and at least two other graduate faculty members. The thesis topic and committee must be approved by the advisor and graduate coordinator. The final version of the thesis must be approved by the advisor, thesis committee and graduate coordinator.

Progression Requirements
  • Students should complete a minimum of two required courses and either CS 53302, CS 63018 or CS 67302 before taking elective courses.
  • Students must maintain a minimum 3.000 GPA. Students earning less than a 3.000 GPA or earning a C grade or lower in two courses will be placed on academic probation.

Graduation Requirements
Minimum Major GPA Minimum Overall GPA
- 3.000
  • No more than one-half of a graduate student’s coursework may be taken in 50000-level courses.
  • Grades below C are not counted toward completion of requirements for the degree.
Program Delivery

Program Delivery

  • Delivery:
    • In person
  • Location:
    • Kent Campus

Examples of Possible Careers and Salaries for Artificial Intelligence - M.S.

Computer and information research scientists

15.4%

much faster than the average

32,700

number of jobs

$126,830

potential earnings

Software developers and software quality assurance analysts and testers

21.5%

much faster than the average

1,469,200

number of jobs

$110,140

potential earnings

Data scientists and mathematical science occupations, all other

30.9%

much faster than the average

33,200

number of jobs

$98,230

potential earnings

Notice: Career Information Source
* Source of occupation titles and labor data comes from the U.S. Bureau of Labor Statistics' Occupational Outlook Handbook. Data comprises projected percent change in employment over the next 10 years; nation-wide employment numbers; and the yearly median wage at which half of the workers in the occupation earned more than that amount and half earned less.
Tuition to Drop by 30% for Kent State Podiatric Medicine Students From Ohio

Kent State University College of Podiatric Medicine students in the Class of 2027 read the physician’s oath during the traditional white coat ceremony that signifies the start of podiatric medical school.

Thanks to a nearly eight-year effort of various Kent State University administrators, Ohio students enrolled in the university’s College of Podiatric Medicine will see a significant reduction in tuition on their next semester’s bill and will graduate with less debt. At its Sept. 20 meeting, the Kent State Board of Trustees approved a revised tuition rate that reduces tuition by nearly $14,000 for Ohio resident students – a decrease of more than 30% – from the current tuition rate effective for the 2024 Spring Semester. Yearly tuition for in-state podiatric medicine students will drop to $32...

Master of Science Thesis Option

Candidates for the Master of Science with a thesis option must successfully complete 24 credit hours of graduate courses in CS, of which at least ten credit hours must be at the 60000 level, and only 12 credit hours can be at the 50000 level. In addition, two credit hours of the Master's Seminar (CS 69191) are required. Only three credit hours of Research (CS 69098) may be counted toward the degree. However, students are permitted to take this course multiple times.

Loud and Proud! Strong Fall Enrollment Numbers Show Kent State on the Rise

New Kent State University students cheer and wave rally towels during 2023 Convocation.

More students have made the commitment to seek a degree from Kent State University and launch their futures as a Golden Flash. The university is celebrating the rise in Kent Campus enrollment for the first time in 10 years along with another strong freshman class and improved retention rates on both the Kent and Regional Campuses. The Class of 2027 has arrived boasting strong academic success and in strong numbers (4,226 students) helping to boost the Kent Campus enrollment by more than 200 students over the previous year.  One of the 10 largest incoming classes in the univer...

Computer Science - M.S.

The Master of Science in Computer Science program provides a comprehensive curriculum that covers a wide range of computer science topics, including software engineering, data science and cybersecurity. With a focus on research and real-world experience, you will be well prepared to tackle complex tech challenges and advance your career.

Contact Us

Apply Now
Request Information
Schedule a Visit
Find All Majors

Program Information for Computer Science - M.S.

Program Description

Program Description

Full Description

The Master of Science degree in Computer Science provides students with an educational and research environment to develop career paths through necessary training with emerging technologies. Graduates have the technical knowledge and skills necessary for success within the information and high technology industries.

The M.S. degree in Computer Science has two culminating options: thesis or non-thesis. Students planning to pursue a Ph.D. degree an/or academic research should select the thesis option. Students planning to pursue applied research and development in industry may select the non-thesis option. The thesis option requires original research and a written thesis. The non-thesis option requires a capstone project and an optional industrial internship.

The Computer Science major includes the following optional concentrations:

  • The Computational Data Science concentration prepares students to process big data. In a spectrum of real-world applications, the collected data (from such sources as mobile devices, GPS, sensor/RFID networks, Internet, social media, etc.) is so large and complex, the traditional data processing tools cannot efficiently and effectively handle it. This concentration focuses on algorithms development, machine learning, computation techniques, network and computing infrastructure and software.
  • The Computer Engineering concentration prepares students to meet the need of computer engineering professionals in the industry for designing and managing emerging smart devices and computer-integrated physical systems with programmable intelligence. Students learn the hardware-software co-design principles and theory, architecture of the associated software and hardware, devices and sensors communication protocols and the interfaces to effectively design, build and evolve such smart devices and computer-driven intelligent physical systems.
  • The Computer Security concentration exposes students to a wide range of topics on the security of computer systems. Students study the vulnerabilities in software and networks and develop algorithms and software to protect data, using digital encryption coding, protected databases and protected computer networking techniques.

Students opting to not pursue a concentration will create a 12-credit hour individualized plan of study with their advisor.

Admissions for Computer Science - M.S.

Admissions

For more information about graduate admissions, visit the graduate admission website. For more information on international admissions, visit the international admission website.

Admission Requirements

  • Bachelor's degree from an accredited college or university
  • Minimum 3.000 undergraduate GPA on a 4.000-point scale
  • Successful completion of high-level algebra, geometry and calculus coursework (equivalent to MATH 12002, MATH 12003 and MATH 21001)1
  • Official transcript(s)
  • GRE scores
  • Résumé
  • Goal statement
  • Three letters of recommendation
  • English language proficiency - all international students must provide proof of English language proficiency (unless they meet specific exceptions to waive) by earning one of the following:2
    • Minimum 71 TOEFL iBT score
    • Minimum 6.0 IELTS score
    • Minimum 50 PTE score
    • Minimum 100 DET score
1

Applicants are strongly recommended to have completed coursework in computer science, including programming, data structures, abstraction, operating systems, combinatorial analysis and discrete structures (equivalent to CS 13001, CS 23001, CS 23022, CS 33211, CS 35101 and CS 46101). Highly qualified students lacking preparation in certain standard areas may be admitted.

2

International applicants who do not meet the above test scores may be considered for conditional admission.

Application Deadlines

  • Fall Semester
    • Application deadline: June 15
  • Spring Semester
    • Application deadline: November 1
  • Summer Term
    • Application deadline: April 1

All application materials (including applicable fee, transcripts, recommendation letters, etc.) submitted after these deadlines will be considered on a space-available basis.

Learning Outcomes

Learning Outcomes

Program Learning Outcomes

Graduates of this program will be able to:

  1. Demonstrate breadth-of-knowledge and understanding of essential facts, concepts, principles and theories relating to advanced topics in computer science.
  2. Conduct literature searches, comprehend advanced research materials and uncover connections between related work and critical evaluation and synthesis.
  3. Perform research, discovery and integration by applying advanced knowledge of computer science.

Coursework

On This Page

Program Requirements

Major Requirements

Major Requirements
CS 69191MASTER'S SEMINAR 2
Core Courses, choose one course each from four out of the five categories: 112
Computational Data Science Category
See courses under Computational Data Science concentration
Computer Engineering Category
See courses under Computer Engineering concentration
Computer Security Category
See courses under Computer Security concentration
Software and Application Category
CS 63005
ADVANCED DATABASE SYSTEMS DESIGN
CS 63100
COMPUTATIONAL HEALTH INFORMATICS
CS 63901
SOFTWARE ENGINEERING METHODOLOGIES
CS 63902
SOFTWARE EVOLUTION
CS 64401
IMAGE PROCESSING
CS 64402
MULTIMEDIA SYSTEMS AND BIOMETRICS
CS 67101
ADVANCED COMPUTER GRAPHICS
CS 67301
SCIENTIFIC VISUALIZATION
CS 67302
INFORMATION VISUALIZATION
Theory and Algorithms Category
CS 63301
PARALLEL AND DISTRIBUTED COMPUTING
CS 64201
ADVANCED ARTIFICIAL INTELLIGENCE
CS 66101
ADVANCED TOPICS IN ALGORITHMS
CS 66105
PARALLEL AND DISTRIBUTED ALGORITHMS
CS 66110
COMPUTATIONAL GEOMETRY
Culminating Requirement
Choose from the following:6
Thesis Option
CS 69199
THESIS I 2
Project Option
CS 69099
CAPSTONE PROJECT
Choose from the following:
CS 69192
GRADUATE INTERNSHIP
CS 69995
SPECIAL TOPICS IN COMPUTER SCIENCE
Computer Science (CS) Graduate course (50000 or 60000 level) with advisor approval
Additional Requirements or Concentrations
Choose from the following:12
Additional Requirements for Students Not Declaring a Concentration
Computational Data Science Concentration
Computer Engineering Concentration
Computer Security Concentration
Minimum Total Credit Hours:32
1

Courses taken for the core cannot be counted again as an elective or concentration course. The list of courses offered each semester, including department-approved special topics, is available in the department's graduate office.

2

Students selecting the thesis option must form a master's thesis committee, which will include the advisor and at least two other graduate faculty members. The thesis topic and committee must be approved by the advisor and graduate coordinator. The final version of the thesis must be approved by the advisor, thesis committee and graduate coordinator.

Additional Requirements for Students Not Declaring a Concentration

Major Requirements
Computer Science (CS) Electives12
Minimum Total Credit Hours:12

Computational Data Science Concentration Requirements

Concentration Requirements
Concentration Electives, choose from the following:12
CS 54001
COMPUTER SCIENCE III - PROGRAMMING PATTERNS
CS 54201
ARTIFICIAL INTELLIGENCE
CS 54202
MACHINE LEARNING AND DEEP LEARNING
CS 63005
ADVANCED DATABASE SYSTEMS DESIGN
CS 63015
DATA MINING TECHNIQUES
CS 63016
BIG DATA ANALYTICS
CS 63017
BIG DATA MANAGEMENT
CS 63018
PROBABILISTIC DATA MANAGEMENT
Minimum Total Credit Hours:12

Computer Engineering Concentration Requirements

Concentration Requirements
Concentration Electives, choose from the following:12
CS 53301
SOFTWARE DEVELOPMENT FOR ROBOTICS
CS 53302
ALGORITHMIC ROBOTICS
CS 53303
INTERNET OF THINGS
CS 53305
ADVANCED DIGITAL DESIGN
CS 53334
HUMAN-ROBOT INTERACTION
CS 63201
ADVANCED OPERATING SYSTEMS
CS 63304
CLUSTER COMPUTING
CS 63305
MULTICORE COMPUTING
CS 63306
EMBEDDED COMPUTING
CS 65101
ADVANCED COMPUTER ARCHITECTURE
CS 65202
ADVANCED COMMUNICATION NETWORKS
CS 65203
WIRELESS AND MOBILE COMMUNICATION NETWORKS
Minimum Total Credit Hours:12

Computer Security Concentration Requirements

Concentration Requirements
Concentration Electives, choose from the following:12
CS 53202
SYSTEMS ADMINISTRATION
CS 53203
SYSTEMS PROGRAMMING
CS 55203
COMPUTER NETWORK SECURITY
CS 57205
INFORMATION SECURITY
CS 57206
DATA SECURITY AND PRIVACY
CS 57207
DIGITAL FORENSICS
CS 57221
INTRODUCTION TO CRYPTOLOGY
Minimum Total Credit Hours:12

Graduation Requirements
Minimum Major GPA Minimum Overall GPA
- 3.000
  • Maximum 12 credit hours of 50000-level courses may be applied toward the degree.
  • CS 61002, CS 61003 and CS 61004 may not be used to fulfill degree requirements.
  • No more than one-half of a graduate student’s coursework may be taken in 50000-level courses.
  • Grades below C are not counted toward completion of requirements for the degree.
Program Delivery

Program Delivery

  • Delivery:
    • In person
  • Location:
    • Kent Campus

Computer Science - M.A.

The Master of Arts degree in Computer Science enables students with a bachelor's degree in any area to enter the many fields that require both computer science skills and skills gained in a student's prior studies. The program requires no prior computer science training and covers a breadth of knowledge in advance computer science topics that can also be used to solve problems in the field of the student's bachelor's degree.

Contact Us

Apply Now
Request Information
Schedule a Visit
Find All Majors

Program Information for Computer Science - M.A.

Learning Outcomes

Learning Outcomes

Program Learning Outcomes

Graduates of this program will be able to:

  1. Demonstrate breadth-of-knowledge and understanding of essential facts, concepts, principles and theories relating to advanced topics in computer science.
  2. Conduct literature searches, comprehend advanced research materials and uncover connections between related work and critical evaluation and synthesis.
  3. Perform research, discovery and integration by applying advanced knowledge of computer science.

Admissions for Computer Science - M.A.

Admissions

For more information about graduate admissions, visit the graduate admission website. For more information on international admissions, visit the international admission website.

Admission Requirements

  • Bachelor's degree from an accredited college or university
  • Minimum 3.000 undergraduate GPA on a 4.000-point scale
  • Successful completion of high-level algebra, geometry and calculus coursework (equivalent to MATH 12002, MATH 12003, MATH 21001)1
  • Official transcript(s)
  • Résumé
  • Goal statement
  • Three letters of recommendation
  • English language proficiency - all international students must provide proof of English language proficiency (unless they meet specific exceptions to waive) by earning one of the following:2
    • Minimum 71 TOEFL iBT score
    • Minimum 6.0 IELTS score
    • Minimum 50 PTE score
    • Minimum 100 DET score
1

Applicants are strongly recommended to have completed successfully coursework in programming, data structures and discrete structures, (equivalent to CS 13001, CS 23001, CS 23022).

2

International applicants who do not meet the above test scores may be considered for conditional admission.

 

Application Deadlines

  • Fall Semester
    • Application deadline: June 15
  • Spring Semester
    • Application deadline: November 1
  • Summer Term
    • Application deadline: April 1

Applications submitted after these deadlines will be considered on a space-available basis.

Coursework

On This Page

Program Requirements

Major Requirements

Major Requirements
CS 61002ALGORITHMS AND PROGRAMMING I 4
CS 61003ALGORITHMS AND PROGRAMMING II 4
CS 61004OPERATING SYSTEMS AND ARCHITECTURE 4
CS 69098RESEARCH 13
CS 69191MASTER'S SEMINAR 2
Computer Science (CS) Electives 215
Minimum Total Credit Hours:32
1

Students enroll in CS 69098 under the direction of a graduate faculty member and develop a master’s project. A master’s project committee must be formed that includes the advisor and at least two other graduate faculty members. The committee and project topic must be approved by the graduate coordinator. The student must present and defend the project before the committee.

2

Maximum 12 credit hours of courses at the 50000 level may be applied toward the degree. Maximum 6 credit hours of 60000 level  project-related course work outside computer science -that are approved by the student's advisor and may count towards the degree.

Graduation Requirements
Minimum Major GPA Minimum Overall GPA
- 3.000
  • No more than one-half of a graduate student’s coursework may be taken in 50000-level courses.
  • Grades below C are not counted toward completion of requirements for the degree.
Program Delivery

Program Delivery

  • Delivery:
    • In person
  • Location:
    • Kent Campus

Subscribe to
© 2025 Kent State University All rights reserved.