Study Data Science
A data science degree is an interdisciplinary program that brings together statistics, computer science, and mathematics to help you find useful meaning in data. It prepares students for roles such as data analyst or data scientist through coursework in machine learning, algorithms, and data visualization.
Accelerated data science degrees allow students to earn a master’s degree in 12-16 months or complete a combined bachelor’s/master’s path in 5 years through 4+1 programs. These intensive, often year-round programs focus on key skills such as machine learning, AI, and data modeling. Some leading options are available at Northwestern, Arizona State Online, and Loyola University Maryland.
In this article, we have reviewed popular on-campus and online accelerated data science degree programs based on speed, flexibility, academic strength, and value.
Accelerated Data Science Degrees
Loyola University Maryland
Accelerated BA/BS-MS in Data Science
The Data Science program at Loyola University Maryland offers an accelerated BA/BS-MS option for current undergraduate students. Students should apply to the MS in Data Science program during the junior year through the Office of Graduate Admissions.
The accelerated Master of Science in Data Science program makes the application process easier and faster for current Loyola undergraduate students while also lowering the total combined tuition cost. This accelerated option gives Loyola undergraduate students a strong way to complete both an undergraduate degree and a master’s degree in only 5 years at Loyola.
Students accepted into the program may take up to 3 graduate-level classes during the senior year. These classes may then be counted toward both completion of the undergraduate degree and the Master of Science in Data Science program. The following 3 graduate-level classes are recommended for cross-application to both the undergraduate and master’s degree:
- CS703 – Programming for Data Science (in place of DS303)
- DS851 – Applied Machine Learning (IS358)
- ST710 – Statistical Computing (ST310)
For students accepted into the Accelerated Program, 2 of the 3 courses taken during undergraduate study must be CS703 and ST710 in order to finish the degree in 1 additional year. It is also recommended that most students take DS851 during undergraduate study.
If a student has already completed one of the undergraduate versions of these courses, that course will be waived from the graduate program by the Academic Program Director (APD), but it must be replaced with an added graduate elective. This rule applies to only 1 of the 3 courses.
All cross-applied courses are billed at the standard undergraduate tuition rate, which lowers the total cost of completing both an undergraduate degree and the Master of Science in Data Science degree at Loyola University Maryland. The remaining graduate-level courses in the program may be taken after successful completion of the student’s undergraduate senior year at the Master of Science in Data Science tuition rate.
Benefits of the Accelerated Program
- The accelerated program offers several benefits:
- Complete both an undergraduate and graduate degree in only 5 years.
- 15% Double Greyhound tuition discount for Loyola alumni.
- Students may count up to 3 courses, or 9 credits, toward both the undergraduate and graduate degrees.
- Application fee waiver.
- Transcript submission waiver.
Prerequisites
To apply for the accelerated program, a student is expected to have completed the following undergraduate courses:
- CS151 – Computer Science through Programming or IS352 – Introduction to Programming in Python
- MA251 – Calculus I
- ST210 – Introduction to Statistics, ST265 – Biostatistics, EC220 – Business Statistics, or PY292 – Research Methods II (with Lab)
- Students are strongly encouraged to take more mathematics courses, such as MA295/CS295 or MA395, MA301, and MA252.
Admission Process
Accelerated admission requires the following:
- Current enrollment as a degree-seeking undergraduate student at Loyola.
- Minimum undergraduate GPA of 3.4 overall and in all Data Science-related courses completed.
- Successful completion of the remaining bachelor’s degree coursework while keeping the minimum GPA requirements.
- Successful completion of the assigned pre-program course sequence as determined by the admissions committee.
Students should apply for accelerated admission program in the academic year right before the final undergraduate academic year, which is the year they expect to complete the undergraduate degree. Students should choose the Fall or Spring academic term that comes after the term in which they will graduate. For example, if a student graduates in Spring 2026, the student should apply for Fall 2026 admission.
Acceptance decisions depend on receipt of official transcripts after graduation. Final transcripts must show that the requirements listed above have been met.
Saint Peter’s University
Accelerated BS to MS in Data Science
As Big Data has grown at a very fast rate in recent years, the need for data scientists has become stronger and more urgent. Saint Peter’s University has developed an advanced academic program to respond to this need and prepare the next group of data scientists.
The Accelerated BS to MS in Data Science program prepares students for leadership roles in finance, retail, pharmaceutical work, consulting, technology, and other sectors that rely on data. Through this Accelerated Program, you can complete your undergraduate degree and a Master of Science in Data Science in 5 years.
This program is intended for students with a background in science, applied science, business, or economics. For preparation, students need to be currently enrolled in a BS program.
The Accelerated BS to MS in Data Science program offers several advantages. The program:
- Speeds up the process of earning an advanced degree.
- Supports a smooth move into a master’s degree.
- Improves students’ value in the Data Science field.
- Helps students save time and money.
The data science degree program uses real-world problems and situations to prepare graduates for roles as strategic thought leaders who use predictive modeling to guide decision-making. Students build a strong understanding of the main technologies used in data science and business analytics, including data mining, machine learning, visualization techniques, predictive modeling, and statistics. Students also practice problem analysis and decision-making.
Through coursework and applied research experiences, students gain practical, hands-on experience with statistics programming languages and big data tools.
Credits and Curriculum
If accepted into the accelerated program, students will take up to 6 Data Science graduate credits in either the fall or spring semester during their last 30 credits. Graduate courses taken while still an undergraduate student are charged at the undergraduate tuition rate and meet course requirements for both the Bachelor’s and Master’s degrees.
The bachelor’s degree will be awarded after successful completion of all undergraduate degree requirements. Note: The University will place the first 6 graduate credits on the graduate transcript after completion of 12 additional graduate credits.
After the bachelor’s degree is completed, students take all remaining graduate courses and must enroll in at least 2 courses in each later semester until the program is finished. All graduate courses are billed at the graduate tuition rate. After successful completion of the remaining graduate credits, the student will receive a Master of Science in Data Science.
Graduate Internship
Completion of an internship related to data science is required for all students, except for those who have 3+ years of professional work experience, those with full-time employment during the program, and those who are taking part in the exchange program. The graduate internship may begin in the 1st semester of classes. Students should speak with their program advisor to find out whether a waiver may be possible.
Admission Requirements
Students may apply to the program after completing 60 credits, and after acceptance, they may take 4 graduate courses (12 credits) during their last 30 credits.
Specific admission requirements include:
- Successful completion of 60 credits.
- Cumulative major GPA of 3.0 or higher, and major GPA of 3.0 or higher, at the time of application and when the BS degree is completed.
- Completion of the BS degree in 4 years or less.
- Submission of the graduate application and a personal statement of 500 words.
- Official transcript(s) will be obtained from Enrollment Services upon completion.
- An interview may be required.
Northwestern University
Master of Science in Data Science
Northwestern’s Master of Science in Data Science helps students build the analysis and leadership skills needed for careers in today’s data-driven world. This accelerated program allows you to complete the degree in just 1 year.
Students in Northwestern’s Master of Science in Data Science learn how to use relational, document, and graph database systems, along with analytics software built on open-source systems such as R, Python, and Go, as well as TensorFlow and Keras for deep learning. Students also learn how to make reliable predictions by using traditional statistics and machine learning methods.
In this accelerated program, you can finish the degree in 1 year through a mix of online and on-campus classes at the downtown Chicago campus. Northwestern’s part-time online data science program has long been known as a leader in graduate data science and analytics programs.
You may choose 1 of 5 specializations: Analytics and Modeling, Analytics Management, Artificial Intelligence, Data Engineering, or Technology Entrepreneurship.
Programming Languages in the Program
The MSDS program includes 3 programming languages: Python, R, and Go. Students in the program gain experience with all 3 languages and may shape their studies toward one language or another based on the specialization they choose.
Python is now the most widely used computer language in data science. It is especially strong in natural language processing and as a client for deep learning platforms.
R has many packages for analytics and modeling and is highly regarded by applied statisticians. It is a strong choice for scientific programming and applied research.
Go is a systems programming language created for today’s multi-processor computers. It works well for building scalable, high-performance systems for data science.
Learning Format
You can take 3 courses per quarter to take part fully in the program. With 2 on-campus courses and 1 online course each term, you have flexibility to continue other daytime activities. Students also benefit from the strong connections built in a cohort and from learning with varied groups of professionals, many of whom hold high-level positions in their fields.
Degree Requirements
The Master of Science in Data Science program requires successful completion of 12 courses to earn the degree:
- 7 core course
- 2 specialization courses
- 2 electives*
- 1 capstone project
Admission Requirements
To pursue a graduate degree at Northwestern, an applicant must hold a U.S. bachelor’s degree from a regionally accredited institution or a foreign equivalent.
Accepted accelerated master’s students begin classes in the fall quarter. Applicants who submit the completed online application form, non-refundable application fee, statement of purpose, resume, and writing sample by the deadline may receive a grace period for outside materials, such as letters of recommendation, official transcripts, and course-by-course evaluations.
A complete application to the School of Professional Studies includes the following parts:
- Online Application
- A $75 non-refundable application fee is required. Payment is made online with a credit card.
- Statement of Purpose
- Resume
- 2 Letters of Recommendation
- Official Transcripts
Maryville University
Master of Science in Data Science
The Accelerated Master of Science with a major in Data Science at Maryville University is a 36-credit-hour program, which includes 12 courses and leads to the Master of Science with a major in Data Science. The 12 required courses are arranged across 4 semesters, with 3 courses completed during each semester. At least 8 Data Science (DSCI) courses at the 500 level or higher are required. The program also allows possible completion in 3 semesters.
With strong attention to experiential learning, the Master of Science in Data Science program uses learning from current or past professional positions as an important part of the active learning curriculum in each graduate course and in the full program goals.
The Accelerated Master of Science in Data Science gives Maryville University undergraduate students majoring in Data Science a special chance to earn a master’s degree in only 1 added year. Through this accelerated option, students may apply 4 courses, or 12 credits, taken during the senior year as part of the undergraduate curriculum toward the master’s degree requirements. In the 5th year of study, students complete an added 24 credits to meet the remaining requirements for the master’s degree.
To qualify for early access to the M.S. in Data Science, students must have at least 75 undergraduate credits. Out of these, at least 20 credits must be earned at Maryville University. In addition, applicants should have a minimum GPA of 3.25. Maryville students entering the accelerated master’s program are not required to submit GRE or TOEFL scores.
Students will also be able to complete coursework toward the following certificate programs:
- Big Data Post Baccalaureate Certificate
- Machine Learning Post Baccalaureate Certificate
- Fundamentals of Artificial Intelligence Post Baccalaureate Certificate
University of Massachusetts Dartmouth
Accelerated BS/MS in Data Science
The accelerated BS/MS program in Data Science at the University of Massachusetts Dartmouth is an integrated degree option that allows qualified students to earn both a Bachelor of Science and a Master of Science in Data Science.
In this accelerated program, you may take up to 9 credits of graduate courses, which means 3 graduate courses at the 500-level or higher, as free or technical electives. These courses will also count toward the MS program, which helps reduce the total time needed to finish the master’s degree.
Interested undergraduate students usually apply for the accelerated program at the beginning of the 2nd semester of the junior year, which is the 6th semester of the BS program.
The accelerated BS/MS program in Data Science is intended for highly motivated and qualified undergraduate students who want to continue into an advanced degree.
- This accelerated BS/MS program offers:
- Greater flexibility in planning courses to complete the prerequisites for advanced study.
- A smooth move into the Master’s degree.
- The opportunity to complete the MS degree requirements within 1 year after finishing the BS.
- A way to improve the efficiency of your college study and academic experience.
The requirements for the BS and the MS degree remain the same as they are for students completing the degrees separately. All students must complete a total of 30 credit hours as described in the MS program. The BS degree must be awarded before the student can be treated as a graduate student.
Students may count up to 9 credit hours, which equals 3 graduate courses at the 500-level or higher, from the list of graduate courses in the combined BS/MS program. These courses may include both required and technical elective courses.
The double-counted courses may be used as either technical or free electives for the BS degree. Double-counted credits must be recommended by the student’s academic advisor and approved by the graduate program director. A grade of B or better is required in any graduate course for it to count toward both degrees.
Admission Requirements
The program is competitive, and admission is based on overall academic performance and a statement of purpose.
To qualify, students must meet the following requirements:
- Be currently enrolled in the BS DSC program at UMassD and not yet have received the undergraduate BS DSC degree.
- Have completed at least 60 credit hours in the BS DSC major.
- Transfer students must have completed at least 2 semesters as a full-time student at UMassD, with a minimum of 30 credit hours.
- Have a minimum cumulative undergraduate GPA of 3.00 and a major GPA of at least 3.00 at the time of application.
- Have completed all lower-division DSC course requirements and at least 9 credits of 300-level coursework in the major.
Students may also be admitted to the BS/MS program through a nomination process. A faculty member may nominate a student with a cumulative GPA of 3.20 or higher by submitting a memorandum of nomination that includes a reason for considering the student. The student must still submit the usual required application materials.
Application Process
Interested students should submit a complete graduate application to the Office of Graduate Studies.
The application should include:
- A completed application form, a brief statement of purpose explaining your reason for graduate study, curriculum vitae, and an unofficial UMassD transcript. A program of study should also be discussed with an academic advisor.
- No Graduate Record Examination (GRE) or TOEFL scores are required.
- The application fee is waived. You should ignore the online payment prompts for the application fee.
Applications will be processed in the same way as the current MS in Data Science program. Applications will be reviewed by the Graduate Committee or the Steering Committee.
Applicants must consult with their academic advisor during the 2nd semester of the junior year or earlier, and they must complete a combined BS/MS program of study that lists all courses to be taken from the senior year through the end of the Master’s program. The program of study must be approved by the faculty advisor and the Graduate Program Director.
Eastern University
Master of Science in Data Science
Eastern’s Master of Science in Data Science is built for students at all experience levels and helps prepare you for many interesting and high-demand careers. In this program, you can gain practical, job-ready skills in leading coding languages, along with important knowledge in data science programming, mathematics, statistics, data analysis, and machine learning.
This program is offered 100% online. The delivery format is self-paced within 7-week online courses. The degree may be completed in as little as 10 months. The program requires 30 credits, which may be finished in as few as 2.5 semesters, with 6 credits taken per 7-week session. Start dates are available every 7 weeks.
The program’s flexible and self-paced structure is designed to provide a strong education at a lower cost than many other programs. Instead of having professors lecture at fixed times, set due dates, require students to learn only from their course materials, or place students in a cohort, Eastern’s faculty have created online, asynchronous, video-based coursework that you can complete at the time that works best for you. This format increases flexibility for students balancing work, family, and personal responsibilities, while also reducing the need for costly faculty involvement.
Students who complete the Master of Science in Data Science will demonstrate:
- An understanding of the moral and scientific challenges connected to current topics in data science.
- The ability to explain complex technical parts of data analysis to both technical and non-technical audiences.
- The ability to use technical knowledge in many real-world problems across different subject areas.
- Strong command of Python, R, SQL, Tableau, and several statistical and machine learning libraries used in data science.
The admissions requirements include the following:
- Completed and signed online application form.
- Official transcript(s) from the undergraduate institution that granted your degree, and from the graduate institution as well if applicable, provided the institution holds accreditation recognized by the U.S. Department of Education.
- Current resume.
- A minimum GPA of 3.0 is preferred, with special attention given to the last 2 years of the undergraduate record. Applicants with a GPA below 3.0 may still be reviewed on a case-by-case basis. Those below 3.0 must submit a GPA letter explaining why the GPA was lower, along with the additional supporting evidence referenced in the source text, which ends before that final item is fully stated.
Is Data Science Still in Demand in 2026?
Yes, a data science degree is still worth it in 2026 if you want to build long-term career value. Even though AI is automating some tasks, there is still strong demand for data scientists who can interpret data, guide decisions, and work alongside automated systems across many industries.
Will AI Replace Data Science?
Data science will not be replaced by AI, but the field is changing in a major way. AI works as a tool that speeds up many routine tasks, such as data cleaning and code generation. As a result, data scientists are moving toward higher-value responsibilities that involve strategy, business context, and careful interpretation of complex information.
This change means the role is moving away from simply carrying out every task by hand and toward guiding the tool in the right direction.
Which is Better, MBA or Data Science?
An MBA is a stronger choice if you want to move more quickly into leadership, strategy, and general management roles. A data science degree is a better option for technical roles that focus on coding, modeling, and AI.
MBA programs usually offer wider business networks and higher median salaries, while data science programs give you focused, high-demand technical skills that are especially useful in technology and analytics-heavy industries.
What is the Best Degree For Data Science?
The strongest degree options for a data scientist include Computer Science, Statistics, Mathematics, and a dedicated Data Science degree. These fields give you the main technical base needed in programming, modeling, and analytical skills.
For higher-level roles, employers often prefer candidates with a master’s degree or PhD. A strong mix of coding and mathematics is very important for success in this field.
Is Data Science Harder than Coding?
Data science requires the same coding skills, along with statistics, machine learning, subject-area knowledge, and the ability to explain findings to non-technical stakeholders. The field is about combining technical skill with business context. For many people, data science offers more flexibility, but it can also feel more spread across different areas.