The Master of Science in Analytics (MSAN) is a full-time, one-year master’s program housed at USF’s downtown San Francisco campus. The program 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.
The 35-unit program concentrates on mathematical and computational techniques in the field of data science. Students learn to acquire, filter, clean, organize, and store data using Python. They use SQL and NoSQL as “glue” between data sources, and generate models using statistical tools such as R and SAS. Course topics include text mining, machine learning, statistical modeling, predictive analytics, econometrics, optimization, marketing analytics, data visualization, business communication, and strategy. View all
Amazon Web Services
The Master of Science in Analytics is proud to have our students develop software and run analyses on Amazon Web Services. Each student receives their own server(s) to manage so they have experience with the mechanics of installing and configuring software.
Our faculty represent the diversity of the big data
industry. They’re traditional academics and data scientists actively working in
the field, using real industry experience to inspire their instruction. Learn more about our faculty.
Analytics Boot Camp
The boot camp is an intensive introduction to, and review of, the foundational knowledge and skills required for sophisticated business analysts and data scientists. Students choose two out of three intensive courses in probability and statistics, computation for analytics, and linear algebra. Additionally, all students take a course in exploratory data analysis, which serves as our program’s formal introduction to the R programming language.
What Faculty and Alumni Say
Analytics Boot Camp (students take 3 of the following classes)
Computation for Analytics (1 unit)
Review of Linear Algebra (1 unit)
Exploratory Data Analysis (1 unit)
Review of Probability and Statistics (1 unit)
Fall Semester (August–December)
Linear Regression Analysis (2 units)
Relational Databases (1 unit)
Business Communications for Analytics (2 units)
Data Acquisition (1 unit)
Introduction to Machine Learning (2 units)
Time Series Analysis for Business and Finance (2 units)
Practicum I (1 unit)
NoSQL Databases (1 unit)
Introduction to Programming in SAS (2 units)
Spring Semester (January–May)
Advanced Machine Learning (2 units)
Business Strategies for Big Data (2 units)
Interview Skills (1unit)
Practicum II (1 unit)
Data Visualization (2 units)
Multivariate Statistical Analysis (2 units)
Distributed Computing (1 unit)
Practicum III (1 unit)
Summer II (May–June)
Special Topics in Analytics (4 units)
Web Analytics (1 unit)
Practicum IV (1 unit)
Tuition and Scholarships
For tuition costs and fellowship opportunities click here.
International students are welcome to apply. International students graduating from the MS in Analytics program are eligible for the STEM extension to OPT (Optional Practical Training).