MS Data Science

2 Years On Campus Masters Program

University of St Thomas

Program Overview

The Master of Science in Data Science at the University of St. Thomas is designed for students and professionals who want to develop expertise in data analytics, machine learning, artificial intelligence, and data-driven decision-making. The program combines statistics, computer science, and business applications to prepare graduates for careers in data science, predictive analytics, and advanced technology-driven roles across multiple industries.

Curriculum Structure

Year 1

Students begin by building a strong foundation in data science methodologies and analytical techniques. Through courses such as Data Analytics, Statistical Modeling, and Data Management, students learn how to collect, manage, process, and interpret large datasets while developing quantitative problem-solving and decision-making skills.

Students also strengthen their technical capabilities through coursework in Programming for Data Science, Machine Learning, and Data Visualization. These courses introduce predictive analytics, modern data science tools, and techniques for transforming complex information into actionable insights.

Year 2

During the second year, students pursue advanced coursework in emerging areas of data science. Courses such as Deep Learning, Artificial Intelligence, and Big Data Analytics provide students with expertise in advanced analytical methods, intelligent systems, and large-scale data processing technologies.

The program culminates in a Capstone Project that allows students to apply machine learning, statistical analysis, and data engineering techniques to solve real-world business or technical challenges. This experience helps students build a professional portfolio while integrating skills gained throughout the program.

Focus Areas

Data Science; Machine Learning; Artificial Intelligence; Big Data Analytics; Predictive Analytics; Statistical Modeling; Data Visualization; Data Engineering; Business Analytics; Applied Data Science.

Learning Outcomes

Develop expertise in data analytics, machine learning, statistical modeling, artificial intelligence, big data technologies, predictive analytics, data visualization, programming, data management, and data-driven decision-making.

Professional Alignment (Accreditation)

The program prepares students for careers in data science, machine learning engineering, business intelligence, predictive analytics, artificial intelligence, and quantitative research. Students gain practical experience working with modern analytical tools and real-world datasets while developing both technical and strategic decision-making skills.

Reputation (Employability Rankings)

The University of St. Thomas School of Engineering is recognized for its strong focus on applied learning, technology innovation, and industry collaboration. Graduates are prepared for roles such as Data Scientist, Machine Learning Engineer, Business Intelligence Analyst, AI Specialist, Data Engineer, and Analytics Consultant, benefiting from a curriculum designed to meet growing workforce demand for data and AI professionals.

Experiential Learning (Research, Projects, Internships etc.)

At the University of St. Thomas, the MS in Data Science program is designed to provide students with hands-on, practical experience that is essential for success in the field. 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 the educational experience.

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

- Data Science Labs: Access to specialized labs equipped with advanced computing resources and software tools like Python, R, and SQL for data analysis and visualization.
- Collaborative Projects: Opportunities to work on group projects that simulate real-world data science scenarios, fostering teamwork and problem-solving skills.
- Internship Opportunities: Strong connections with local businesses and organizations provide students with internship placements, allowing them to apply their skills in professional settings.
- Field Trips: Organized visits to tech companies and data-driven organizations to gain insights into industry practices and network with professionals.
- Research Facilities: Access to research centers focused on data analytics, machine learning, and artificial intelligence, where students can engage in cutting-edge research projects.
- Libraries and Resources: Comprehensive library services with access to a wealth of academic journals, databases, and resources specific to data science.
- Industry Partnerships: Collaborations with industry leaders that enhance the curriculum and provide students with exposure to current trends and technologies in data science.

Progression & Future Opportunities

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

- Career Services: The university offers dedicated career services, including resume workshops, interview preparation, and networking events with industry professionals.
- Employment Statistics: Over 90% of graduates secure employment within six months of graduation, with starting salaries averaging around $85,000.
- University–Industry Partnerships: The program has established partnerships with leading companies such as Target, Medtronic, and Wells Fargo, providing students with internship opportunities and real-world projects.
- Accreditation: The program is accredited by the Higher Learning Commission, ensuring that your degree holds long-term value in the job market.
- Graduation Outcomes: Graduates have reported high job satisfaction and career advancement, with many moving into leadership roles within a few years of completing their degree.

Further Academic Progression: After completing the MS in Data Science, students have the option to pursue a Ph.D. in Data Science or related fields, which can open doors to academic positions, advanced research opportunities, or specialized roles in data analytics. Additionally, graduates may choose to obtain professional certifications in areas such as machine learning or data engineering to further enhance their expertise and career prospects.