Data Science University of Minnesota

Overview

The Data Science programme at the University of Minnesota provides students with the technical expertise required to navigate the modern data landscape. This interdisciplinary degree prepares graduates to identify complex patterns and trends that drive decision-making processes across various global industries.

Data scientists play a vital role in interpreting diverse information types, including text, images, video, and audio. By mastering these skills, students learn to make accurate predictions that help organisations improve products and refine customer service strategies through evidence-based insights.

Why Data Science at University of Minnesota?

The curriculum is uniquely interdisciplinary, integrating coursework and faculty from fifteen distinct academic departments. Key contributors include the Department of Computer Science and Engineering, the Department of Mathematics, and the Department of Industrial and Systems Engineering.

Students enjoy a high level of flexibility, with numerous elective options that allow for deep dives into specific areas of interest. The programme also supports interdisciplinary projects and offers a double major pathway specifically paired with Computer Science for those seeking broader technical expertise.

The College of Science and Engineering provides a vibrant community with specialised student groups. Learners can engage with the Internet of Things (IoT) Collaborative or the UMN Blockchain group, fostering professional growth and networking opportunities outside the traditional classroom setting.

Facilities and research initiatives are led by distinguished faculty, including Regents Professors who direct the university's Data Science Initiative. This environment ensures that students are exposed to cutting-edge developments in artificial intelligence and machine learning throughout their studies.

Tuition Fee Breakdown

• International fee: USD 41512 per year
• National fee: USD 41512 per year
• Local fee: USD 18626 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum draws from multiple departments to provide a well-rounded education in the field. Modules may include:

• Data Science
• Optimization for Machine Learning
• Ethics in Computing
• Data Mining
• Regression and Statistical Computing
• Operations Research for Data Science

Careers with Data Science

Graduates are well-equipped for a variety of technical and analytical roles in the evolving job market. The programme prepares students for high-demand positions that involve managing large-scale data architectures and developing sophisticated machine learning models.

Common career paths for graduates include:

• Business intelligence analyst
• Data mining analyst
• Data scientist
• Data warehouse architect
• Database administrator
• Machine learning engineer

The field is experiencing significant growth, with thousands of new roles projected in the coming years. Graduates find success in both commercial industry and academic research, leveraging the diverse opportunities provided by the university's extensive corporate and research partnerships.