Data Science (MS)

The master of science in data science (msds) offers a rigorous curriculum designed to align with the rapid advancements in data science (ds) and artificial intelligence (ai) technologies. 

In 12 months, the program integrates courses in analytics, machine learning, deep learning, cloud computing, large language models, solution communication, advanced AI topics, data engineering, and more. Through a combination of theoretical foundations with approximately nine months of hands-on practical application, including real-world practicum experiences, students are prepared to thrive in the dynamic and ever-evolving realms of data science and artificial intelligence.

A Career in Artificial Intelligence with Data Science

• Master’s degrees launch AI professionals to new heights in their careers. Employees with AI-related master’s degrees are in high demand across a range of industries, and the salaries they’ll earn are higher than those of their counterparts who hold only undergraduate degrees. Explore career paths, skillsets, and outcomes for AI professionals.

Technically Challenging Curriculum

• Since we hosted the first cohort of MSDS in 2012, the MSDS curriculum has been meticulously curated and regularly updated to align with the latest industry trends and advancements. Throughout the program, students will develop proficiency in a wide range of analytical skills, gain expertise in computational and engineering tools, and delve deeply into advanced machine learning (ML), deep learning (DL), and artificial intelligence (AI) methodologies.

Practicum

• An integral part of the program is that all students are guaranteed participation in a practicum program with our external partners aimed at offering real-world working experience. With a dedicated commitment of 16 hours per week spanning approximately nine months, students directly engage with business and research challenges to apply their acquired skills in data science, data engineering, and AI development. These practicum project placements extend beyond the confines of the San Francisco Bay Area, providing students exposure to a diverse group of companies and industries across different geographic locations.

Previous partners include Meta, Reddit, Atlassian, Block Inc., PG&E, UCSF, Stanford Medical, Upwork, BlackRock, and AWS. See a full list of historical partners and projects below:

• All students gain real-world experience for approximately nine months of the program (16 hours/week) tackling data science and analytics problems at organizations around the San Francisco Bay Area and beyond. Each year, roughly 50 companies pitch their projects to our students, and students rank their preferences based on the project proposals (past and current partners include those shown below). Students with complementary strengths are matched up to form a team. To ensure the success of the projects, each team is actively mentored by a faculty member and a company mentor who participate in regular meetings to supervise and provide technical and mathematical expertise.

Hands-on Experience with Industry Leaders

Following an initial hypothesis, students typically engage in data acquisition, exploratory data analysis, feature extraction, model development and evaluation, as well as oral and written communication of results. Class schedules are set so that students work on their projects two dedicated days per week throughout the practicum.

• Practicum begins in mid-October.
• Students devote 16 hours a week to practicum work on average.
• Projects may be paid or unpaid.

Faculty

• Our faculty represents the fundamental multidisciplinary nature of the big data industry. They’re teacher-scholars and practitioners actively working in the field, using real industry experience to inspire their instruction.