The Analytics Program is a full-time, one-year Master’s program that resides at USF’s downtown San Francisco campus, less than four miles from the USF main campus. The program is designed for students with a strong background in math, computer science, engineering or economics who seek the specific techniques and tools involved in analytics — and the business skills to apply this knowledge effectively and strategically.
This 35-unit program grounds you in both the techniques and skills required to analyze structured and unstructured big data to derive meaning and drive business decisions. Graduates become data scientists and analysts in finance, marketing, operations, business intelligence, or other groups generating and consuming large amounts of data. Students study topics such as: data mining, machine learning, statistical models, predictive analytics, econometrics, optimization, risk analysis, data visualization, business communication, and management science. You learn to acquire, filter, clean, organize, and store data using Python and SQL/NoSQL as "glue" between data sources and statistical tools such as R and SAS. The focus is on applying mathematics, statistics, and computer science to solve real problems.
Practicums are special features of the program that provide you with the professional skills, experiences and networking needed to succeed in a business setting. Each semester, students engage in a project working with an industrial partner (some of which are paid internships). Students have worked with Mozilla, SurveyMonkey, PayPal, and Thomson Reuters, among others.
Analytics Boot Camp (Beginning July 8, 2013)
Three five-week intensive courses (computational, applied math and economics) with exposure to modern statistical packages, SQL, R and Python, review of probability and statistics, linear algebra, linear regression, and review of basic micro and macroeconomics, including pricing and demand, uncertainty and consumer modeling.
USF's MS in Analytics program is proud to have our students
develop software and run analyses on Amazon Web Services (e.g., Amazon Elastic Compute Cloud, Amazon DynamoDB, and Amazon Relational Database). Each student gets their own server or servers to manage so they get experience with the mechanics of installing and configuring software. Students have access to vast resources, albeit in bursts, to solve big data projects and typically “submit” their projects by e-mailing a URL on their server to the professor for grading.
2013/2014
Summer (Beginning July 8)
Computation for Analytics (1 unit)
Review of Linear Algebra (1 unit)
Introduction to Data-Driven Business Strategies (1 unit)
Review of Probability and Statistics (1 unit)
Fall Semester (August 20 - December 4)
Module 1
Linear Regression Analysis (2 units)
Exploratory Data Analysis (1 unit)
Business Communications for Analytics (2 units)
Data Acquisition (1unit)
Module 2
Machine Learning (2 units)
Time Series Analysis for Business and Finance (2 units)
Practicum I (1 unit)
Distributed Databases (1unit)
Intersession (January 2 - 17)
Introduction to Programming in SAS (2 units)
Spring Semester (January 21- May 8)
Module 1
Text Mining (2 units)
Business Strategies for Big Data (2 units)
Interview Skills (1unit)
Practicum II (1unit)
Module 2
Data and Information Visualization (2 units)
Multivariate Statistical Analysis (2 units)
Distributed Computing (1unit)
Practicum II (1unit)
Summer II (May 19 - June 27)
Analytics for Social Networks (2 units)
Marketing Analytics (2 units)
Web Analytics (1 unit)
Practicum III (1 unit)
Tuition and Scholarships
For tuition costs and fellowship opportunities click here.
International students are welcome to apply. Students graduating from USF's MS in Analytics program are eligible for the STEM extension to OPT (Optional Practical Training).
