FAQs
Your Answers Are Here
Answers to the most frequently asked questions about the Data Science program can be found on this page. If you have further questions please contact us.
Program Details
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This is a full-time, 12-month program. The program starts in early July and continues through the end of June in the following year.
Students opting for the Data Engineering concentration will complete an additional semester of coursework (18 months total).
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There are no night classes. There is no part-time option at this time.
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There is no online option at this time. At USF, you will interact frequently in person with both your instructors and the other students in your cohort.
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Our 2024–2025 cohort will be approximately 90 students in size. In most classes, we run lectures in two or more sections to keep class sizes small. There are no teaching assistants leading class lectures or class discussions in our program.
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Classes run during the day Monday through Friday, with four classes running simultaneously each module. (A “module” is approximately half a semester). Two days per week are devoted to practicum work. The practicum starts in mid-October.
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Because students come from a variety of academic backgrounds, students take three five-week intensive review courses and pass a linear algebra exam starting in early July to bring everyone's level of understanding up to a similar level. All students take EDA & Visualization as well as Computation for Analytics and Probability & Statistics. The boot camp is a way for students to quickly decide whether they have the appropriate background and the proper motivation to succeed. Every year, a few students do not continue with the program after the end of boot camp.
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The Data Institute (DI) develops innovative programs to foster the next generation of data scientists and serves as the umbrella organization for data science research and programming at USF. The Institute supports three major initiatives which include AI and Healthcare, Data Ethics, and Environment and Social Impact. Each year, a number of practicum projects in these areas are available to MSDS students in partnership with the Institute.
Current MSDS students are eligible to participate in some Data Institute certificate classes free of charge. MSDS alumni receive a discount on DI certificate courses as well.
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No. Our curriculum is specifically designed for our MSDS students. Students take courses together as a cohort and all students must complete all 35 units of required coursework here at USF in order to graduate.
Financing Your Education
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See USF's Graduate Student Costs. For financial aid info, visit our Financial Aid page.
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The Master of Science in Data Science program awards a limited number of partial scholarships to our best applicants. For the class of 2024–2025, the median scholarship (among students given scholarships) was $6,300 (range $4,000–$15,000). You do not need to fill out a separate application to be considered for a scholarship; all applicants are considered.
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No. Teaching assistantships and research assistantships are typically reserved for doctoral students at research-oriented institutions. The time that might ordinarily be allocated, in a doctoral program, to supporting a faculty member's research or to helping a professor teach a course is allocated to practicum projects in our program, though we have a growing number of research-focused projects. Some practicum positions are paid and some are unpaid, depending on the company.
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Tuition is due at the beginning of each semester. The university offers a payment plan for those who wish to make monthly payments.
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Students are not permitted to work during the program with the exception of their practicum projects. Due to the accelerated nature of the program, there is no time for outside jobs and students find it necessary to devote 100% of their time to coursework and practicum work.
Nine Month Practicum
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One of the major advantages of the MSDS program at the University of San Francisco is that students work on real projects with real companies for approximately 9 months out of their 12-month experience. Descriptions of past years’ projects and partner companies are listed on our website.
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No. The program curates data science projects for our students and matches students with companies based on interest, skill set, company needs, and project.
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The decision to provide compensation for practicum work is up to each individual company. Approximately 50 percent of projects are paid, and 50 percent are unpaid.
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Since the program's inception in 2012, over 90% of all graduates have received an offer of employment within three months of graduation.
Program Admission: Requirements & Timetables
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Applicants must have high grades in prior coursework in probability and statistics, linear algebra, and computer programming (Python, Java, or C++). Applicants must hold a bachelor’s degree. Typically, though not always, our applicants majored in mathematics, engineering, economics, statistics, or computer science. We welcome applicants from all bachelor's degree backgrounds.
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You must have completed all required prerequisite courses before the start of the program. This is an accelerated master's program and there is no time to take extra courses. You may apply with courses in progress provided that they will be completed by the time the program begins.
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Yes. You can take these as a visiting student prior to applying for the MSDS program, if you do not require a student visa to study in the U.S. USF is not able to issue I-20s for visiting students. Please consult the catalog for more information on mathematics and computer science courses.
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We encourage prospective students to examine the offerings of accredited colleges or universities local to them. Many applicants complete our prerequisites at a community college. If you are unable to complete the courses locally, the following institutions offer one or more courses via online or distance learning format that will satisfy our prerequisite requirements. Courses at these institutions are taken for a grade on a transcript and require a proctored final exam.
Linear Algebra
- University of North Dakota
- University of Illinois at Urbana-Champaign
- Louisiana State University
- Harvard Extension
- Distance Calculus
- UCSD Extension
- University of Massachusetts Global
Inferential Statistics
- University of Illinois at Urbana-Champaign
- UC Berkeley Extension
- UCLA Extension
- Outlier
Programming
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You should take MATH 230 (Elementary Linear Algebra). The Department of Mathematics typically offers this course every year in the fall semester. MATH 202 (Linear Algebra and Probability) satisfies neither the linear algebra nor the inferential statistics prerequisite for the MSDS program.
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You should take MATH 101 (Elementary Statistics). The Department of Mathematics typically offers this course every semester. There are other courses at the university that satisfy the inferential statistics prerequisite, such as MATH 102 (Biostatistics), MATH 103 (Statistics for the Social Sciences), MATH 360 (Probability & Statistics), or ESS 200 (Statistics). We will also accept two-course sequences in probability theory and statistics for mathematics majors as satisfying the inferential statistics prerequisite. For example, at the University of San Francisco, this sequence is composed of MATH 370 (Probability with Applications) and MATH 371 (Statistics with Applications).
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You should take CS 110 (Introduction to Computer Science I). The Department of Computer Science typically offers this course every semester. CS 110 features Python, a preferred programming language for the MSDS program. However, our more competitive applicants have also taken the equivalent of CS 112 (Introduction to Computer Science II), a second course in computer programming that typically features Java and requires students to build more sophisticated and larger programs.
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Programming experience is necessary to be successful in the MSDS program. While practical experience is valuable, we require that applicants complete at least one programming course at an accredited college or university. Note that HTML, web design, PHP, Microsoft Excel, VBA, etc. might be valuable, but they do not count towards programming experience. We require knowledge of programming languages like Python, Java, C#, or C++. If you do not have prior experience in Python, we recommend that all applicants complete at least one course in Python as that is the language used most in the program.
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No. Given the uncertainties surrounding online coursework, and the failure of many online courses to provide a mechanism by which student code is evaluated and checked for plagiarism, applicants should show coursework on transcripts from accredited academic institutions in order to have a competitive application. Certificate coursework can serve as a supplement to courses taken for college credit.
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We do not have a minimum GPA requirement, though we are generally looking for GPAs of 3.0 and above and we examine transcripts carefully. The median undergraduate cumulative grade point average is usually approximately 3.3.
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Our typical acceptance rate is approximately 25 - 35%.
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We primarily use the Python programming language.
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Yes. Our deadline for priority scholarship consideration is December 5. It is still possible to receive a scholarship if your application is received after December 5, but the availability of scholarship funds after that date is uncertain.
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Yes. Starting in December, we process applications on an ongoing basis. Some applicants are summarily denied. Some applications are placed on hold until the final March 1st application deadline. Other applicants are interviewed and admitted to the program before the application deadline. In general, we advise prospective students who are highly motivated to join our program to apply as early as possible in the admissions cycle.
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We do not provide a pre-review of any application. We cannot comment on an individual's chances of admission as our applicant pool changes from year to year.
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No. Our priority deadline is for priority scholarship consideration and does not guarantee an early decision.
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Yes. An important part of our admissions process is an online technical interview with a member of our faculty admission committee. The interview consists of questions drawn from our prerequisite subjects (linear algebra, statistics and programming) and also serves as a chance for applicants to ask questions about the program.
International Students
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Yes, the program welcomes international applicants. Learn more about our current cohort and the students’ backgrounds on our Class Profile page.
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Please view the minimum test score requirements.
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English language exams are waived for applicants who have completed a bachelor's degree, a master's degree, or one year or more of studies in a degree program in English at a higher education institution on the exempted countries list. Our program does not waive the English language exam requirement for applicants with degrees completed in countries other than those included on the exempted list.
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The graduate admissions office provides a list of organizations that offer financial resources for international students. You can find more information on financial aid or loans available to international students on the Financial Aid Office’s website.
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International graduates typically apply for OPT (Optional Practical Training) after they graduate. MSDS qualifies as a STEM major. International students apply for CPT (Curricular Practical Training) during the academic year for their practicum assignment.
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Yes, USF requires that proof of funds is submitted at the time you apply in order to expedite the I-20 process if admitted. This is very important, especially given the short turnaround time between admissions decisions and the program start date in early July for the MSDS program.
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If you plan to finance your education with a loan, you will need to obtain a letter from your bank stating that they will provide a loan for the needed amount if you are admitted. Upload this letter to the certification of finances section of the application. If you are unable to provide a letter, please contact asapplication@usfca.edu for other options.
Data Science, MS
101 Howard Street
San Francisco, CA 94105