MSDS Prerequisite and Application Tips for Non-STEM Majors

Applying to the M.S. in Data Science (MSDS) program can feel intimidating if your undergraduate degree wasn’t in a STEM field. One of the most common concerns we hear is about the program prerequisites: what they are, why they matter, and how to complete them. The good news is that students from all majors are welcome, and many of our strongest applicants come from non-STEM backgrounds. 

To help you navigate the process with confidence, MSDS student ambassadors who successfully made the transition share their insights and advice.  

Required Prerequisites 

To be eligible for admission, MSDS applicants must complete four prerequisite courses: 

• Statistics
• Programming
• Linear Algebra
• Single-variable Calculus (Calculus I or II)

If you’re missing one or more of these, conditional admission is possible. In that case, your offer letter will include instructions to complete outstanding courses before matriculation. 

Linear algebra is one of the most commonly missing prerequisites among non-STEM majors, so plan ahead if it’s not in your background. 

Two Ways to Complete Your Prerequisites

Incorporate Courses Into Your Undergraduate or Post-Baccalaureate Coursework 
If you discover data science late in your undergraduate journey, you can still integrate prerequisites into your upcoming semester. Courses can be in progress at the time you apply.

Completing prerequisites early can: 

• Strengthen your application
• Demonstrate readiness for a rigorous graduate program
• Reduce the number of conditions after admission

Use UVA’s Data Science Boot Camps 
If you are missing calculus or linear algebra, the School of Data Science offers focused boot camps designed specifically for MSDS readiness:

• Calculus for Data Science Boot Camp
• Linear Algebra for Data Science Boot Camp

These intensive courses help you prepare quickly, reinforce essential skills, and ensure you start the program strong. 

Applicant Advice From Current Students

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Isabel Delgado

B.A. in Fine Arts 2022, The George Washington University

• Know your why. Be clear about why you want to pursue data science and what you hope to achieve. Describe the skills or topics you're most interested in learning during the program and your goals for the future. This will show your commitment and your motivation for applying.
• Complete (most of) your prerequisites before applying. If your background is not in STEM, completing a majority of the prerequisites will strengthen your application. It shows that you're capable of handling the rigorous program and can boost your overall GPA. I took my prerequisites through my local community college, but most universities allow you to enroll in classes as a non-degree-seeking student. 

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Karina Diva Mehta

B.A. in Commerce 2023, University of Delhi

• Clarify prerequisites early. If you have any questions about prerequisites or whether your prior coursework meets the requirements, don’t hesitate to email or check with the UVA admissions team. I found them extremely helpful in guiding me to use the correct courses for credit transfer, which reduced stress and ensured my application was accurate.
• Use Boot Camp to strengthen and refresh your skills. The MSDS Boot Camp is designed to prepare you for the program’s R and Python requirements. Complete it within the recommended timeframe, and take some time before classes start to revisit key concepts. While resources like GeeksforGeeks or W3Schools can help, refreshing your fundamentals ensures you’re ready for the master’s courses.
• Ensure your recommendations highlight different strengths. When selecting recommenders, aim for letters that showcase complementary aspects of your skills and experience. One recommender might focus on your technical expertise and analytical problem-solving, while the other emphasizes leadership, mentorship, and teamwork. This approach provides a well-rounded picture of your abilities and ensures that each letter adds new insight rather than repetition.
• Connect your past experience to future impact. Frame your achievements in terms of potential contributions to the University, School of Data Science and the wider data science community. For example, mentoring recruits or improving data systems can translate into leadership in group projects, peer learning etc.  

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Mauricio Torres

B.A. in Economics 2025, George Mason University

• Attend info sessions. The virtual events on the UVA Data Science website helped me understand prerequisites and the full application process. They answered questions I didn’t even know I had.
• Manage your timeline. Aim for the priority deadline, but don’t rush. Breaking the process into pieces helps you stay authentic and avoid rushing: prerequisites, personal statement, recommendations. 

Final Thoughts

Students from all majors thrive in the MSDS program. In fact, our Fall 2025 cohort includes students from 41 different undergraduate majors. Data science is inherently interdisciplinary, and your unique background is an asset, not a disadvantage.

Completing your prerequisites thoughtfully, clarifying your goals, and planning ahead will help you submit a strong, compelling application no matter your academic starting point. If you have questions about the prerequisites or the application process, the admissions team is here to help.

Learn more about the full-time, in-person Residential MSDS at the University of Virginia. Request more information, connect with Admissions, or start your application today.

M.S. in Data Science, Residential