Academics

The Master of Data Science (MDS) program provides flexible learning paths, with both full-time and part-time options, tailored to meet your unique academic and professional demands. Regardless of the pathway chosen, all students enjoy equal access to our rich, comprehensive curriculum and the collective wisdom of our distinguished faculty.

To earn the MDS degree, students must complete 52 units. This includes ten core courses, which form the backbone of data science principles; three elective courses, offering an opportunity to delve into areas of personal interest within the field; and finally, a capstone project that allows students to apply their knowledge to real-world problems, synthesizing and showcasing their learning.

Upon completion of the program, graduates will be equipped with a robust blend of technical expertise and professional skills. This combination prepares you for a successful career trajectory, enabling you to seamlessly transition into the evolving domain of data science and make your mark.

The Capstone Project is the culmination of the MDS program, providing students with the opportunity to work on real-life data science problems with industry partners. The projects are comprehensive in scope, allowing students to demonstrate the breadth and depth of their knowledge in data science. The project is designed to develop an empirically-driven solution to sponsoring organizations and covers the full spectrum of the analytic process, including data gathering, manipulation, visualization, analysis, and interpretation of results. Students work in small groups to put concepts and techniques together and put them into action.

A successful capstone project involves several key elements, including clearly defining the problem to be solved or the question to be answered, conducting exploratory data analysis, data cleaning, and data visualization to gain insights into the dataset, and describing the methods and techniques used to analyze the data and address the problem or question. This may include machine learning models or statistical analyses.

Additionally, a successful capstone project should present the results of the data analysis, including any visualizations or graphs that help to convey the findings, and discuss the implications of the findings. This should include a discussion of any limitations or areas for future research. Students should also provide the code used for data analysis and modeling, along with detailed documentation, explaining the code and how it was used.

Finally, students create a final presentation or report that effectively communicates the findings to a non-technical audience. The ability to effectively communicate technical findings to non-technical audiences is a critical skill for data scientists.

Sample projects:

• Deploying Open Source LLM into Municipality.Prison Mental Health Assessment during Pandemic
• Utilizing Sound Waves for Geolocation Analysis
• Statistical Analysis on Language Development in Infants
• Social Determinants on Health and Long Covid
• Utilizing AI to Categorize and Diagnose Autoimmune Diseases from Raw Images
• Multi-Model Analysis on Re-incarceration in the U.S.

In the Master of Data Science (MDS) program, career development is a key focus. We prioritize the success of our students by offering tailored support through our dedicated Career Services team, which emphasizes individualized career coaching.

Our team provides personalized career guidance, helping students identify their career goals and navigate their job search. Services include one-on-one coaching, resume and cover letter reviews, and customized job search strategies.

To enhance career competitiveness, we offer professional development opportunities that align with industry demands, supported by our team’s expertise in current job market trends. Students gain practical experience through internships, capstone projects, and networking events like career fairs and alumni gatherings, all designed to help build connections and improve career readiness.