Data Science involves extracting information or learning from data to generative predictive scenarios of the future. Methods include combining multiple sources of data, applying artificial intelligence and machine learning techniques, and modeling data using statistical methods. After earning a master's degree, students will be qualified to work in industry and government where their skills will help support decision-making.
According to the U.S. Bureau of Labor Statistics, employment is projected to grow 22 percent from 2020 to 2030, much faster than the average for all occupations. About 3,200 openings are projected each year, on average, over the decade. Many of those openings are expected to result from the need to replace workers who transfer to different occupations or exit the labor force, such as to retire.
Loyola’s University Maryland’s MS in Data Science is a part-time, self-paced program for working professionals from all academic and industry backgrounds. The Loyola MS in Data Science is tailored to meet the needs of our students. Our curriculum is designed for students to earn their degree in 34 credits (12 courses) – 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. All courses are designed and facilitated by Loyola faculty members, creating a unique, relevant and robust learning experience for students.
The Loyola MS in Data Science is offered in a fully online format with 15-week courses. Our approach to online learning is highlighted by small class size and a personalized student experience. Online courses are primarily asynchronous and include opportunities for faculty and student interaction.
The Master of Science in Data Science offers students a thorough data science educational experience through a thirty-four-credit program, eleven three-credit courses and one one-credit course. The program includes a data science core, which is at the nexus of business, computer science, and statistics. This degree blends computer science and statistics courses to render students adaptable to any domain with rigorous statistical and computational skills. Following the five-course core, there are seven additional courses: two statistics courses; two computer science courses; one elective from business, statistics, or computer science; a one-credit design course for the research project; and a capstone research project conducted with a partner in local industry/government/non-profit. The required statistics courses develop students' modeling skills, and the computer science course exposes students to machine learning and artificial intelligence.
The broad knowledge and transferable skills coupled with a strong sense of values, ethics, clear communication skills, and high student-faculty engagement, typical of a liberally educated student, are evident in the Data Science master's program. The program integrates ethics as a fundamental tenet of several courses, reflecting one of the program's primary learning aims, and buttressed by students' participation in practicum experiences where they partner with local businesses, industry, and not-for-profits.
Students who currently enrolled in the analytics micro-credential program or business analytics specialization will earn the SAS certification recognizing their ability to leverage SAS analytical tools for data preparation, analytics, and visualization.
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.