

MS in Data Science
- Private University
College of Arts and Sciences
MS in Data Science at USF Overview
Duration | 1 year Get Curriculum |
Tuition & Fees | ₹50.12 Lakh Get Fees details |
International Students Admission Website | Go to Website |
Official Career Service Website | Go to Website |
Course Level | PG Degree |
MS in Data Science at USF Fees
The fee breakup of the University of San Francisco MS in Data Science includes the first-year tuition fee and cost of living. The cost of living will include expenses like rent for accommodation, meals, and other utilities. The first-year tuition fees MS in Data Science is USD 56,525. Students must note that the total expenses are subject to vary, depending on the additional charges set by the University of San Francisco. Students can check the table given below to know more about University of San Francisco MS in Data Science fee breakup.
| Fees components | Amount (for 1 year) |
|---|---|
| Tuition & fees | INR 50,12,072 |
| Fees components | Amount (for 1 year) |
|---|---|
| Insurance | INR 3,32,069 |
| Transportation | INR 1,36,729 |
MS in Data Science at USF Curriculum
For detailed information regarding the University of San Francisco program at MS in Data Science, click on the green button below. The curriculum PDF provides all important information students may need to know related to the course including subjects taught, available electives and other course-related content. The PDF also provides a semester-wise breakup of the overall course structure.
Download exam sample paper
MS in Data Science at USF Entry Requirements
- No specific cutoff mentioned
- No specific cutoff mentioned
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- Applicants must have completed aa bachelor's degree in any field from an accredited college or ubniversity
- Applicants with academic or professional backgrounds in math, computer science, engineering, finance, economics or equivalent skills are encouraged to apply
- Applicants must have completed the following prerequisite Courses : Inferential Statistics, Linear Algebra ,a social science course,Computer Programming – (ava, Mathematica, Matlab, Python or C++: ability to read/write data from files, write structured programs in a high-level language), Familiarity with basic data structures (list, dictionary, stack, queue)
- In addition to the above requirements, department strongly recommend courses in calculus and data structures

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Out of 10
- Marks - 90/120
-
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Out of 10
- Marks - 61/90
- NA
- Marks - 6.5/9
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- Marks - 115/160
- NA
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MS in Data Science at USF Rankings
| Rank | Rank Publisher |
|---|---|
| #110 | |
| #1201 |
MS in Data Science at USF Placements
| Particulars | Statistics (2022) |
|---|---|
| Highest Salary | USD 1.80 Lakh |
| Median Salary | USD 1.25 Lakh |
| % Batch placed | 90 |
| Internship Available | Yes, All students gain real world experience for nine months of the program (15 hours/week) tackling data science and analytics problems at organizations around the San Francisco Bay Area and beyond |
University of San FranciscoStudents Ratings & Reviews
- 100% students never faced discrimination in this university
MS in Data Science at USF Highlights
- The Master of Science in Data Science (MSDS) is a full-time, one-year program housed at USF’s downtown San Francisco campus
- The 35 unit program begins in early July every year and features a modern, open-source-focused curriculum for students who seek the technical expertise required to become data scientists and analysts, and the business skills to apply this knowledge effectively and strategically
- Courses Include:-
Application Development
Machine Learning
Statistical Modeling
Natural Language Processing
Business Strategy
Design of Experiments
Distributed Computing
Deep Learning
Data Visualization
Business Communication
MS in Data Science at USF Scholarships
Class Profile
| Average class profile for this course | |
|---|---|
| Student Age | 25 |
| Percentage of International Students | 64 |
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MS in Data Science at USF Contact Information
2130 Fulton Street,San Francisco,California,USA 94117-1080
San Francisco ( California)




