College of Sciences and Humanities
Department of Computer Science
www.kent.edu/cs

About This Program

Step into one of today’s fastest growing fields and learn to design intelligent systems that solve complex, real-world problems. Through hands-on projects and cutting-edge topics like machine learning, data science and robotics, you will build the technical expertise employers demand. Graduating with both practical experience and advanced knowledge, you will be ready to lead innovation across industries shaping the future. Read more...

Contact Information

• Arvind Bansal | gradinfo@cs.kent.edu |
  330-672-9047

• Connect with an Admissions Counselor

Program Delivery

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

Examples of Possible Careers and Salaries*

^{* 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.}

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: Minimum B grade in high-level algebra, geometry and calculus courses (equivalent to MATH 12002, MATH 12003, MATH 21001)¹
• 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.

Program Requirements

Major Requirements

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

• 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 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.

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.