Program Overview
The Master of Science in Data Science (MSDS) is a full-time, one-year program housed at USF’s downtown San Francisco campus.
Commencing annually in early July, this comprehensive 35-unit program offers a state-of-the-art curriculum in AI and data science. Specifically designed for students with aspirations to excel as data scientists, machine learning engineers, data engineers, and AI engineers, the program covers a wide array of courses, including Data Processing, Visualization, A/B testing, Python, SQL, NoSQL database management, Spark, AWS, and other cloud computing tools, Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Large Language Models, and other advanced topics. Furthermore, the program places a strong emphasis on fostering business acumen that’s essential for strategically applying this knowledge across industries, including a course on data science-specific resume writing and interview preparation.
Data Science Boot Camp
The program begins with our boot camp, an intensive review of the foundational knowledge and skills required for success in the MSDS program. Students complete accelerated review courses in probability & statistics and computation for analytics and also must pass a linear algebra competency exam in order to move forward in the program. Additionally, all students take a course in exploratory data analysis & visualization for a total of three courses and one linear algebra exam in the introductory summer semester.
Nine Month Practicum
Practicum projects allow students to work for 16 hours per week for approximately nine months tackling data science problems at organizations in the San Francisco Bay Area and beyond. All students are guaranteed a practicum placement.
Partnership with Leading Cloud Computing Providers
Our partnership provides students with significant support in the form of credits and trainings to gain experience across a variety of technologies. Select student projects may also be featured on the providers' web pages. Our partnership includes top cloud computing providers Amazon Web Services (AWS) Educate, Google Cloud Platform (GCP) for Education, Databricks University Alliance, and MongoDB for Academia.
Class Schedule
Classes are held Monday through Friday during the day, with four classes running simultaneously each module (half a semester). Two days per week are devoted to practicum work, which begins in mid-October. Students take classes together as a cohort and most classes are split into two sections to keep class sizes small.
Due to the accelerated nature of the program, students find it necessary to devote 100% of their time to coursework and practicum work. Therefore, work outside the practicum is not permitted.
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- Application Development
- Machine Learning
- Statistical Modeling
- Natural Language Processing
- Business Strategy
- Design of Experiments
- Distributed Computing
- Deep Learning
- Data Visualization
- Business Communication