Data Science MS

2 Years On Campus Masters Program

University of the Pacific

Program Overview

The University of the Pacific's Master of Science in Data Science (MSDS) is a 32-unit, STEM-designated graduate program designed to prepare students for careers in data analytics, predictive modelling and artificial intelligence. Delivered through a flexible hybrid format over four semesters, the program combines statistics, linear algebra, programming, machine learning and data visualization with an industry-sponsored capstone project that gives students experience solving real-world analytics problems.

Curriculum Structure

Year 1: Students establish a strong foundation in data science through programming, machine learning, data visualization and analytical methods. Core courses such as Analytics Computing for Data Science (ANLT 212), Introduction to Machine Learning (ANLT 221) and Introduction to Data Visualization (ANLT 232) help students develop skills in data preparation, computational analysis, predictive modelling and visual communication. Students also participate in the Data Science Socratic Lab, where they discuss emerging technologies and practical applications.

Year 2: Students advance their technical expertise through specialized electives, applied analytics and industry-oriented projects. Courses such as Machine Learning for Data Science (ANLT 222), Relational Databases (ANLT 242) and Customer Analytics (ANLT 274) develop their ability to manage complex datasets, build predictive models and generate actionable insights. Students complete the Data Science Capstone Project (ANLT 282), working on a real-world analytics problem and applying their knowledge to practical industry challenges.

Note: The program consists of 32 units across four semesters. The university provides a structured curriculum, but individual course sequencing and elective selections may vary.

Focus Areas: Data Analytics, Predictive Modelling, Artificial Intelligence, Machine Learning, Data Engineering, Data Visualization, Statistical Analysis, Customer Analytics, Healthcare Analytics, Database Management, Data Preparation and Business Intelligence.

Learning Outcomes: Analyze numerical, categorical and textual data using appropriate statistical and machine learning techniques, apply modern programming and data engineering skills, develop and evaluate predictive models, organize and manage large datasets, communicate analytical findings through effective visualizations, and apply scientific methods to solve real-world data challenges.

Professional Alignment (Accreditation): The program emphasizes practical industry preparation through its experiential capstone project, Data Science Socratic Lab and applied coursework. Students gain opportunities to work on industry-sponsored analytics projects with organizations and develop skills relevant to data science, predictive analytics and artificial intelligence. The program is STEM-designated, making eligible international graduates potentially eligible for the STEM OPT extension.

Reputation (Employability Rankings): The University of the Pacific offers students opportunities to learn from experienced academic professionals and industry experts associated with organizations such as Google, PayPal and Charles Schwab. Its capstone projects provide practical exposure to real-world business and analytics challenges, with industry connections including organizations such as the Sacramento Kings, Charles Schwab and Gallo Winery.

Experiential Learning (Research, Projects, Internships etc.)

At the University of the Pacific, the Data Science MS program is designed to provide students with hands-on experience that bridges the gap between theory and practice. Students engage in real-world projects, utilize cutting-edge technology, and collaborate with peers to solve complex data challenges. The program emphasizes experiential learning through various facilities and tools that enhance your educational journey.

Here are some key aspects of experiential learning in the Data Science MS program:

- State-of-the-Art Labs: Access to dedicated computer labs equipped with advanced software and hardware for data analysis, machine learning, and statistical modeling.
- Software Proficiency: Gain experience with industry-standard tools such as Python, R, SQL, Tableau, and TensorFlow, ensuring you are well-prepared for the job market.
- Collaborative Projects: Participate in group projects that simulate real-world data science scenarios, allowing you to work alongside fellow students and faculty on meaningful research.
- Internship Opportunities: The program encourages internships with local businesses and organizations, providing invaluable experience and networking opportunities in the data science field.
- Field Trips: Engage in field trips to tech companies and data-driven organizations, offering insights into industry practices and trends.
- Research Institutes: Collaborate with faculty on research initiatives at the Center for Data Science, where you can contribute to innovative projects and gain exposure to cutting-edge research.
- Library Resources: Utilize the extensive resources at the University Library, including access to databases, journals, and research materials specific to data science.

Progression & Future Opportunities

The Data Science MS program at the University of the Pacific equips graduates with the skills and knowledge needed to excel in a rapidly growing field. Alumni have successfully transitioned into roles such as Data Analyst, Data Scientist, Machine Learning Engineer, and Business Intelligence Analyst. With a strong foundation in data analysis and practical experience, graduates are well-prepared to meet the demands of various industries:

- Career Services: The university offers dedicated career services, including resume workshops, interview preparation, and networking events, to help students connect with potential employers.
- Employment Statistics: Graduates of the Data Science MS program have a high employment rate, with many securing positions within six months of graduation. The average starting salary for data science roles in the region is around $85,000, reflecting the high demand for skilled professionals.
- University–Industry Partnerships: The University of the Pacific has established partnerships with leading tech companies and organizations, providing students with internship opportunities and real-world projects that enhance their learning experience.
- Accreditation Value: The program is accredited by the Western Association of Schools and Colleges (WASC), ensuring that the education you receive meets high standards and is recognized by employers.
- Graduation Outcomes: The program boasts a strong track record of successful graduates who have gone on to work for top companies in technology, finance, healthcare, and more.

Further Academic Progression: After completing the Data Science MS program, students have the option to pursue further studies, such as a Ph.D. in Data Science or related fields, which can open doors to advanced research positions or academic careers. Additionally, graduates may choose to specialize further by obtaining certifications in areas like machine learning, artificial intelligence, or big data analytics, enhancing their expertise and marketability in the job market.