Data Science MS

About the MS in Data Science at Loyola

Data science is a multi-disciplinary field combining techniques from mathematics, computer science, and statistics to organize, analyze, visualize, and extract useful information from data.

From business to medicine, neuroscience to sports, marketing to public policy, the explosion of huge mountains of data impacts every imaginable field. The surge of available data has multiplied the need for professionals who can understand and clearly communicate — to experts and non-experts alike — what the numbers tell us.

Whether your background is in computer science or another field, the master’s in data science will enhance your skills toolkit and allow you to gain a broader understanding of how to use these tools in practical applications, whatever your field.

Program Structure

The MS in Data Science is offered fully on campus at the Loyola Lake Shore campus; classes are held during the day and early evening. The program can be completed full-time or part-time on either the thesis or non-thesis track.

  • Thesis track students finish in 4 semesters while completing an original research project; the final semester of the thesis track is all research

  • Non-thesis track students complete the program in 3 semesters finishing with a data science capstone project

Are you a current Loyola undergrad?

This program is eligible for an Accelerated Bachelor's to Master's degree. Earn a Master’s with only one extra year of study following the completion of your eligible undergraduate degree.

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Why Choose Loyola for Your Data Science Master’s Degree?

Flexible options

The master’s in data science is offered in both a thesis and non-thesis track to fit your career and completion goals.

The master’s program is taught by a multidisciplinary faculty of highly-qualified experts with both academic and industry experience in data science. You will have many opportunities to interact and collaborate with faculty across disciplines on applied research projects such as applying data science tools in biology, detecting misinformation on the web, and identifying cyberbullying in social media.

The MS in Data Science is a collaboration of the Department of Mathematics and Statistics and the Department of Computer Science. A degree in data science, combining topics in statistics, math, and computer science ensures that you will develop a broad range of in-demand job skills that can be applied in many domains. While data science ranks among the top degrees for jobs in technology and STEM fields, a strong foundation in data skills has become essential in almost every occupation.

Meet the Faculty

Loyola is proud to have talented and nationally-recognized scholar-teachers as part of our diverse community of exceptional faculty, students and staff. Loyola faculty are known for their commitment to teaching, the dissemination of knowledge through innovative and interdisciplinary scholarly research, and a commitment to social justice and cura personalis, or care for the whole person. Visit the department faculty and staff directory to learn more about the teachers and mentors involved with the Data Science MS program.

Faculty

Curriculum and Program Outcomes

While courses for the Data Science MS program may vary from semester to semester, Loyola’s extensive Academic Catalog will always house the official listing of courses, programs of study, academic policies, degree requirements, and specialization or concentration options.

Additionally, this resource will provide Data Science MS learning outcomes, showcasing the commitment to specific skills and growth graduates can expect to achieve following completion of the program.

2023-2024 Catalog
Browse Academic Catalog

Costs, Scholarships, and Aid

Loyola University Chicago is committed to making your graduate and professional studies a reality. Our Cost & Financial Aid page can help better inform you about the costs and potential funding opportunities through scholarships, loans, and aid for graduate and professional education.

If you are a current Loyola undergraduate or recent alum, you may be eligible for a Returning Rambler discount. Learn more and see if you qualify on our Returning Rambler Scholarship page.

Tuition and Costs

The estimated tuition and fees for the Data Science MS totals $34950.00, or 30 credit hours at a cost of $1,165.00 per credit hour. Please note that tuition and fees for all of Loyola's academic programs are subject to change.

For more detailed information about tuition and fees, and a breakdown of how these costs are calculated on a yearly basis, please visit Tuition and Fees from the Office of the Bursar.

The Graduate School Scholarships

Information about funding opportunities within The Graduate School can be found on The Graduate School website.

Data Science MS Scholarships

The Data Science graduate program awards up to two graduate assistantships among applicants with complete applications submitted by February 15 and targeting a fall semester start.

Appointments and Events

Whether you’re just beginning your search, in the midst of the application process, or eager to explore our graduate and professional programs, our admissions staff is here to assist you every step of the way.

Schedule an Appointment

The Graduate School offers graduate open houses, information sessions, individual appointments, open Zoom and text sessions, and a multitude of other ways to get to know us better.

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Visit and Connect With Us

With our visit opportunities, you can tour our beautiful Chicago campuses and learn more about Loyola's ties to one of the most prestigious cities in the world.

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Application Process

Application Deadlines

The available start terms and corresponding application deadlines for the Data Science MS are listed below. Please keep in mind that both the application and the required materials must be submitted by the specified deadline.

Fall
Rolling admission
Consideration for merit funding: February 15
Final deadline: August 1

Spring
Rolling admission

Decisions are provided within a week of complete application submission.

Application Requirements

Application requirements for the Data Science MS include:

  • Official Transcripts

  • 2 Letters of Recommendation

  • 3.0 Minimum GPA

  • Statement of Purpose

Prerequisite Course Requirements

Admission to the Data Science MS program requires successful completion of the following courses:

  • One year of Calculus equivalent to MATH 131 and 132 (Calculus I and II) or MATH 161 and 162 (Calculus I and II)

  • One course in Introductory Statistics equivalent to STAT103 (Fundamentals of Statistics), STAT203 (Statistics), or STAT335 (Introduction to Bio-statistics)

  • One course in data structures equivalent to COMP231 (Data Structures and Algorithms for Informatics) or COMP271 (Data Structures I), preferably with R and/or Python

Statement of Purpose Details

Please describe previous experiences that motivated your interest in Data Science and a problem you would like to solve using Data Science skills.

Official Documents

Official transcripts are those that are sent directly by the college/university to Loyola University Chicago. Transcripts sent by the student to Loyola are considered unofficial documents, and while they may be utilized for initial review of your application, official transcripts are still required. Official documents should be sent by the institution to gradapp@luc.edu.

International Applicant Requirements

An official English language proficiency exam is required for international applicants whose native language is not English. If you have non-U.S. educational credentials, you are required to submit an official transcript evaluation. The transcript evaluation cannot be waived.

Please visit our International Applicant Requirements page for specific information regarding the application process for international students.

International Applicant Requirements
Start Your Application

Applying online to the Data Science MS program is a swift, uncomplicated, and cost-free process. After submission, you can proceed to send and upload any additional requirements.

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