Kent State University Data Science – The MSc in Data Science program is an interdisciplinary program sponsored by the Department of Computer Science and the Department of Mathematical Sciences. This program is a DHS STEM designated degree program [30.7001]. It places specific computational skills in a broader interdisciplinary space in computer science and related fields of statistics, including databases, data mining, machine learning, and big data. It uses scientific methods, processes, algorithms and systems to extract knowledge and insights from multiple structured and unstructured data. One can think of data science as a fusion of methods and ideas from analytics, statistics, databases, big data, artificial intelligence, numerical analysis, graph theory, and visualization, by finding information in data and applying that information to real-world problems. It combines experience, theory and computational techniques to make data-driven decisions. The program offers a thesis and a non-thesis track. The program provides opportunities for students to expand their interdisciplinary space beyond math and CS to other disciplines.
Formal course requirements are listed in the university catalogue. Students entering the MS in Data Science program must have an undergraduate degree with a 3.0 out of 4.0 GPA from an accredited college or university and complete the following mathematics and computer science courses prior to beginning the program. If all courses are not completed at the time of application, acceptance into the program requires completion of the remaining courses before beginning the program.
Kent State University Data Science
In addition to standard university requirements, admission to the program requires an overall 3.0 GPA in prerequisite courses and, for students whose native language is not English, proof of English proficiency. Evidence of English proficiency may be a transcript showing at least one academic year of full-time attendance at an English-medium university, or TOEFL IBT 71 or PBT 525. IELTS scores may be submitted in lieu of TOEFL scores. Minimum IELTS requirement is 6.0.
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We accept applications year-round and review applications as they arrive. It is important to complete and submit your application as soon as possible. It may take a few weeks for your application to be sent and processed.
Formal course requirements are listed in the university catalog, but in total, students must complete 30 credits, of which 18 credits are required, 6 credits are electives, and 6 credits are culminating experience.
For more information on postgraduate admissions, visit the postgraduate course website. For more information on international admissions, visit the website of the Office of Global Education. Data science is about turning data into knowledge. By applying interdisciplinary principles from information science, statistics, and computer science, data science attempts to sort through vast amounts of data and extract information needed for decision making.
Online, you can track who viewed which version, when, where, and with what level of engagement. Altmetrics uses this data to supplement traditional measurements of the impact and influence of scholarly works. For example, altmetrics can measure the number of times a work has been downloaded, shared, featured in the news or commented on, or the distribution of a global audience.
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Big data refers to the enormous leap in data volume that has occurred in the 21st century due to recent technological advances. Big data research aims to understand the issues surrounding interdisciplinary and big data and to develop solutions for managing, analyzing and using large amounts of data.
Machine learning is the ability of computers to improve decisions through experience. The more the user interacts with the machine, the more data it receives; And the more data it gets, the more accurate its judgment of relevance becomes.
Natural language processing research explores the use of artificial intelligence and linguistics to develop systems that can use context to “understand” text and speech content. Computer-enhanced ability to understand the meaning of words can be used to improve the accuracy of information retrieval. The advent of advanced technologies for capturing and analyzing data has created unprecedented opportunities for business analytics professionals across all industries and organizations. Combine your business skills and analytical acumen as a professional with a Master’s in Business Analytics (MSBA). By earning a master’s degree in business analytics, you will increase your ability to survive in the highly competitive market of analytics professionals. Watch the MSBA webinar.
MSBA courses offered in fall and spring, 100% online and in person – no GRE/GMAT required! Tri-Focus STEM Program
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Today’s business language relies on information and data management. The State University MSBA program provides you with comprehensive analytical knowledge, balancing the technical, analytical and business expertise you need so you can derive useful information from data and make strategic business decisions.
With the KSU MSBA, you’ll gain the technical, analytical, communication, decision-making, and leadership skills necessary to be a successful business analyst. In-person and online courses include an integrated capstone analytics program and internship options for additional professional development through our on-site Career Services office dedicated to business students. Along with our STEM designation, international F-1 students are eligible for OPT (Optional Practical Training), which allows them to gain additional career experience while in state.
Fall and spring admissions are highly competitive. As applications are reviewed on a rolling basis throughout the admissions cycle, early application is strongly encouraged. In addition to the online application form and fee, you must submit:
We look forward to seeing you on our MSc in Business Analytics, so please make sure your application meets the requirements above.
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Because of its diversity, our MSBA accepts students from a variety of academic backgrounds, including business, engineering, computer science, and other science disciplines. Prior exposure to coursework and/or work experience in information/computer systems, applied statistics/mathematics, and business is expected.
If you would like to learn more about our MSc in Business Analytics or better understand the content of our Data Analytics course, contact us today. Kent State University’s online MS in Digital Science – Data Science degree combines an introduction to data science with a general survey of digital studies, information systems, and computer science. The curriculum offers great flexibility in electives, and students can choose to take on-campus courses if they want part of their online degree experience. Kent State University, a research-intensive public university in Kent, Ohio, requires GRE scores and a minimum GPA of 3.0 from applicants. The program does not specify that prerequisite courses are required.
Data science focuses on the analysis and modeling of data required by organizations and the application of statistical and semantic analysis techniques to process structured, semi-structured and unstructured data to meet these needs.
The Data Science track is the focus of the MSc in Digital Science and covers data analysis, modeling and processing of structured, semi-structured and unstructured data using statistical and semantic analysis. Focus is on identifying and meeting organizational needs. Including the capstone course, the program’s 32 credits can be completed in two years.
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Students in the Master of Digital Science program must take three core courses covering data architecture, semantic analysis techniques, and knowledge organization systems and services. All students complete a capstone program in digital science to complete their degree. Additionally, students can study computer science, communications, statistics, geographic information systems, health informatics, educational technology, management information systems, library and information science, knowledge management, user experience design and technology. Data science concentrations are encouraged to take courses that help meet program objectives to meet organizational needs through the processing, analysis, and modeling of structured, semi-structured, and unstructured data.
Students complete the degree in two years and pay just under $999 per credit for a total of 32 credits, or $32,000 for the full degree.
The program is usually completed 100% online and does not require a campus visit. However, online students who choose to come to Kent (and those who live in the area) can choose to take on-campus courses if they wish. The course is taught asynchronously, in which teachers prepare material for weekly study blocks such as lectures, activities, quizzes and group discussions that can be chosen to be completed at any time of the week. Classes begin in the fall and spring semesters and part-time study is possible. The project usually takes two years to complete.
Kent State’s Master of Science in Digital Science with Data Studies concentration program may be the right choice for data scientists who want to gain a broad education in how society uses digital technologies to organize and process all kinds of information. Drawing on the research expertise and large faculty of this comprehensive research university to study topics of interest, students can take advantage of a large number of elective courses in many disciplines.
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