How do I apply?
The online application and application requirements can be found on the Master of Science in Data Science Admission page.
What is the deadline for admission?
Students are admitted to the Data Science program in either the fall or spring semester. The deadline for submitting a completed program application and all supplemental documents for fall entry is August 1, and the deadline for spring entry is December 1. At the discretion of the department, applications will continue to be reviewed after the deadline on a space-available basis.
Are GRE/GMAT scores required?
No, GRE/GMAT scores are not required to complete a program application.
Are there any prerequisites for the program?
The Data Science program is open to students from all undergraduate majors. Students are expected to have taken a college-level introductory statistics course. Students without an introductory statistics course can be satisfied by taking Loyola's preparatory course, DS510 - Applied Business Statistics or another approved introductory statistics course.
What is the cost of the program?
The tuition costs and payment options can be found on the Graduate Fees page.
Are there scholarships available?
Yes, merit-based scholarships are awarded to Master's of Data Science students based on prior academic excellence. All students are eligible to receive merit-based scholarships, and every student who completes an application for admission is automatically considered for merit scholarship funding. No separate application is required, and you will be notified of your merit scholarship at the time of admission.
Loyola offers a number of assistantships to new and continuing graduate students in a wide range of professional areas. Each opportunity provides a stipend for which you will be remunerated bi-weekly, and a scholarship which is applied at the start of your assistantship contract. This combination of stipend and scholarship is typically split 50/50 to provide you the greatest pre-tax benefit. More information can be found on the Graduate Assistantships page.
Am I able to work while pursuing this program?
Yes, the Data Science program is a part-time, self-paced program for working professionals from all academic and industry backgrounds. The Data Science program is tailored to meet the needs of our students. Our curriculum is designed for students to earn their degree in 31 (or 34) credits - allowing for faster time to completion and return on investment. Students manage their program at their own pace and typically complete their degree in 2-4 years. The Master of Science (MS) in Data Science allows five years for students to complete all degree requirements. All courses are designed and facilitated by Loyola faculty members, creating a unique, relevant and robust learning experience for students.
How are the courses delivered?
For students beginning in Fall 2021 and thereafter, all courses will be offered 100% online. Depending on the instructor, the course may be offered either synchronously or asynchronously.
How is the capstone project structured?
A strength of the program is the required two-semester capstone practicum, which could include a summer internship. The practicum is an independent or group project that uses the data science techniques acquired during the program in an applied manner to solve a practical problem with a local partner. In the first semester, students design the project and present their plan to the program's board; this could be part of a paid internship. The program director works to develop opportunities by developing a strong advisory board, comprised of industry, government, and not-for-profit representatives. In the second semester, students implement their project and present the results of the project to the board for approval.
What can I do professionally once I graduate?
After earning a master’s degree, students will be qualified to work in industry and government where their skills will help support decision-making. Jobs that utilize these skills include data scientists, business analysts, domain-specific managers, computer systems analysts, data mining analysts, and business intelligence specialists.
What specializations do the professors have?
Information about faculty and staff can be found on the Faculty & Staff page.