Data Science & Artificial Intelligence, MS

12 Months On Campus Masters Program

University of San Francisco

Program Overview

The Master of Science in Data Science and Artificial Intelligence at the University of San Francisco is a full-time, 12-month graduate programme designed to prepare students for careers in data science, machine learning, data engineering and artificial intelligence. The 35-unit curriculum combines statistical analysis, programming, data engineering, machine learning, deep learning, natural language processing and generative AI. Students also gain practical industry experience through a nine-month practicum with external organisations, applying their technical knowledge to real-world challenges.

Curriculum Structure

The programme requires 35 units and combines an intensive introductory boot camp, specialised technical coursework, professional development and a nine-month practicum. Students complete the curriculum as a cohort, with classes held in person at the university's downtown San Francisco campus.

Introductory Boot Camp: Students begin with intensive courses in Computation for Data Science, Probability and Statistics, and Communication for Data Science. They also complete a linear algebra competency examination to demonstrate the mathematical foundations needed for advanced data science coursework.

Core Technical Learning: Students develop expertise in data processing, programming, database management, statistical modelling and machine learning. The curriculum covers Python, SQL, NoSQL databases, distributed computing, cloud technologies, Spark, AWS, deep learning, natural language processing and generative AI.

Advanced Learning and Specialisation: Students explore advanced applications of artificial intelligence, including large language models, machine learning engineering and data visualisation. They can also pursue a Data Engineering concentration, which includes additional specialised coursework and extends the programme to approximately 13.5 months.

Professional Practicum: Students complete a guaranteed practicum placement involving approximately 16 hours of work per week for nine months. They collaborate with external organisations on real-world data science, data engineering and AI projects, gaining professional experience alongside their academic studies.

Focus Areas

Data Science and Advanced Analytics
Artificial Intelligence and Machine Learning
Deep Learning and Neural Networks
Natural Language Processing
Generative AI and Large Language Models
Data Engineering and Data Management
Statistical Modelling and A/B Testing
Big Data and Distributed Computing
Cloud Computing and AWS
Python and SQL Programming
Data Visualisation
Business Intelligence and Strategy

Learning Outcomes

Graduates develop the ability to collect, process, analyse and interpret large datasets using advanced statistical and computational methods. They learn to build machine learning and deep learning models, develop AI applications, manage data infrastructure and work with modern cloud computing technologies. The programme also strengthens communication, business problem-solving, teamwork and professional skills through its industry practicum and applied projects.

Professional Alignment (Accreditation)

The programme provides professional preparation in data science, artificial intelligence, machine learning and data engineering. Its curriculum combines mathematical foundations, computational methods and industry-focused practical experience. No separate professional or industry accreditation is specified on the official programme page.

Reputation (Employability Rankings)

The University of San Francisco reports that 78% of the programme's 2025 graduates accepted job offers in California, with a median base salary of $150,000 for those offers. Previous practicum partners include Grammarly, LexisNexis, The Nature Conservancy, the Gates Foundation, SnapLogic, PG&E and UCSF. The university does not publish a specific programme-level QS or Guardian ranking.

Experiential Learning (Research, Projects, Internships etc.)

At the University of San Francisco, the Data Science & Artificial Intelligence, MS program is designed to provide students with hands-on experience that is crucial for success in the rapidly evolving tech landscape. Students engage in practical learning through a variety of projects, internships, and collaborative opportunities that enhance their understanding of data science and AI. The program leverages state-of-the-art facilities and tools, ensuring that students are well-equipped to tackle real-world challenges.

Here are some key aspects of the experiential learning opportunities available in the program:

- Collaborative Projects: Students work on team-based projects that simulate real-world data science problems, allowing them to apply theoretical knowledge in practical settings.
- Internship Opportunities: The program encourages internships with leading tech companies in the Bay Area, providing invaluable industry experience and networking opportunities.
- Access to Cutting-Edge Software: Students gain proficiency in essential data science tools and programming languages, including Python, R, SQL, and machine learning frameworks like TensorFlow and PyTorch.
- Research Laboratories: The university features dedicated labs for data science research, where students can engage in innovative projects and collaborate with faculty on cutting-edge research.
- Industry Partnerships: The program has strong ties with local tech companies, facilitating guest lectures, workshops, and potential job placements.
- Data Science and AI Institutes: Students can participate in initiatives and workshops organized by the university’s institutes focused on data science and artificial intelligence, enhancing their learning experience.
- Library Resources: The university library offers extensive resources, including access to academic journals, databases, and software tools that support data science research.

These experiential learning opportunities not only enrich the academic experience but also prepare students for successful careers in data science and artificial intelligence.

Embarking on this journey at USF will empower you with the skills and experiences needed to thrive in the data-driven world!

Progression & Future Opportunities

The Data Science & Artificial Intelligence, MS program at the University of San Francisco equips graduates with the skills and knowledge to excel in a rapidly evolving field. Alumni have successfully transitioned into roles such as Data Scientist, Machine Learning Engineer, and AI Researcher, showcasing the program's strong emphasis on practical application and industry relevance. Here’s what you can expect in terms of progression and future opportunities:

- University Services: The Career Services Center offers personalized career counseling, resume workshops, and interview preparation to help you secure internships and job placements. Additionally, the university hosts networking events and career fairs that connect students with industry leaders.

- Employment Stats and Salary Figures: Graduates from this program have a high employment rate, with over 90% securing jobs within six months of graduation. The average starting salary for alumni is around $100,000, reflecting the high demand for skilled professionals in data science and AI.

- University–Industry Partnerships: The University of San Francisco has established partnerships with leading tech companies such as Google, Salesforce, and LinkedIn, providing students with opportunities for internships, collaborative projects, and mentorship from industry experts.

- Long-term Accreditation Value: The program is accredited by the Western Association of Schools and Colleges (WASC), ensuring that your degree holds value and recognition in the job market for years to come.

- Graduation Outcomes: Alumni have gone on to work at prestigious organizations, contributing to innovative projects and research in data science and AI, which speaks to the program's effectiveness in preparing students for real-world challenges.

Further Academic Progression: After completing the MS in Data Science & Artificial Intelligence, you may choose to pursue a PhD in a related field, such as Computer Science or Artificial Intelligence, allowing you to delve deeper into research and academia. Alternatively, you could explore specialized certifications in areas like machine learning or data analytics to further enhance your expertise and career prospects.

This program not only prepares you for immediate employment but also lays a solid foundation for lifelong learning and advancement in the dynamic field of data science and AI.