Data Science MS Program

A dataset can reveal patterns, raise questions, and challenge assumptions—but only when you have the tools to interpret it. Michigan Tech’s multidisciplinary MS in Data Science combines computing, mathematics, engineering, and business perspectives so you can study how information becomes useful evidence across different fields. Whether researching machine learning, designing algorithms for forestry, or conducting computational social science, a Data Science degree is a smart investment in your future.

The Accelerated Master's Program is available for current Michigan Tech students.

Who is This Program For?

This interdisciplinary MS in Data Science is ideal for those who enjoy working with complex data and want to connect analytical methods with meaningful questions.

Consider this master's program if you like developing or evaluating computational approaches to data analysis; examining patterns in technical, scientific, or organizational information; and connecting data methods with an application area such as engineering, health, or business.

What You'll Study

In this flexible program, you'll bring together computing, quantitative analysis, business, engineering, and mathematical sciences to investigate complex datasets. Research sensors, develop pattern recognition algorithms, engineer intelligent machines, interpret medical data to determine risk, make predictions using data to improve the power grid, and more.

You'll learn how to apply the appropriate data-science method for the problem you're trying to solve.

Where You'll Apply Your Knowledge and Skills

Data science helps organizations move from a large collection of observations to a question they can investigate. You can use your degree to build and evaluate models, detect patterns in sensor or operational data, examine health-related risk information, or interpret complex energy and business datasets.

Data scientists often find employment in healthcare systems, technology companies, national laboratories, and financial services. The Mayo Clinic uses analytics and informatics in healthcare, IBM researches AI and data-intensive systems, and Argonne National Laboratory applies computational methods to science. Your degree focus, then, will shape your future workplace.

  • Delivery Options

    • Accelerated: MS
    • On-Campus: MS

Data Science Program Details

Choose a specific degree option or delivery type to learn more about the data science program at Michigan Tech. For international students, Data Science is a designated STEM program.

On-Campus Programs

Additional Program Information

Want to learn more about data science at Michigan Tech? Visit the department for more information:

Contact

Graduate Director

Laura Brown

 

Sample Areas of Interest

Select areas of interest to help customize your data science MS. Sample areas include:

  • Bioinformatics
  • Sensor Networks
  • Statistics
  • Biogeochemistry

View full listing for this program

Application Process and Admissions Requirements

Using a holistic approach, our graduate admissions team reviews applications on an individual and ongoing basis. Fill out our free graduate application online to apply to any of our programs. Official transcripts and scores are not required for the initial application, but you will need to upload them later.

Accredited by HLC

Michigan Tech has been accredited by the Higher Learning Commission (HLC) since 1928. We offer over 125 graduate certificates, master's degrees, and PhD programs to provide our students and the world with what tomorrow needs.

Who You'll Learn From and Work With

Learn from faculty who use data and computation to study questions in different disciplines. Their interests include machine learning, algorithms applied to forestry, and computational social science.

These diverse perspectives can help you understand how the same analytical tools are adapted to very different kinds of evidence.

 

 

Faculty Spotlight

Laura Brown

Laura Brown
Associate Professor,
Computer Science

"It’s 80 percent and 20 percent."

Big Data is a big deal, and data mining depends on the skills of computer scientists. While 80 percent of our time is juggling this data, it’s what we learn in that other 20 percent that makes all the difference. Brown and her colleagues work with the 80 to push what’s possible in that 20.

Program Faculty