Data Science

Earn your data science degree online

Master's Grad certificate

UW-La Crosse's online Master of Science in Data Science and Graduate Certificate in Data Science are designed to help you advance in today’s data-driven world.

Designed for working adults, these fully-online programs provide the skills you need to organize, analyze and interpret complex data.

Whether you're aiming to grow in your career or pivot into a high-growth field, our programs equip you with the tools to drive informed decision-making using advanced analytics, data visualization and machine learning. Both programs are offered through Wisconsin Online Collaboratives.

Program highlights

100% online
No GMAT or GRE required
Flexible pacing
Expert instruction

A program within Mathematics & Statistics

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Master of Science

Online Master’s in Data Science

Data is transforming every industry—and skilled professionals are in high demand. UWL’s 100% online MS in Data Science gives you the flexibility to learn on your schedule and the expertise to stand out in the job market. Gain hands-on experience with Python, machine learning, predictive modeling, data visualization and more. This program delivers the credibility and career impact you need to move forward.

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Graduate Certificate

Online Data Science Certificate

Whether you’re launching your career in data science or building on existing expertise, UWL’s Graduate Certificate in Data Science gives you a direct path to advancement. In just five courses (15 credits)—three required and two electives—you’ll gain practical, career-ready skills tailored to your goals.

Ready to move forward? Request information today and see how UWL can help you achieve your next big step.

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What is data science?

Data science is an interdisciplinary field that involves gathering, analyzing, and interpreting large volumes of data to help organizations make smarter, faster decisions. This process often uses cutting-edge technologies, including artificial intelligence, to uncover valuable insights. Today skilled data science professionals are in demand across every industry.

Career outlook

What distinguishes UWL's graduate programs in data science?

Flexible, online

Access your classroom online, anywhere from nearly any device. You don’t need to be online at a certain time to participate in class or complete assignments.

Accredited

The Master of Science in Data Science is approved by the University of Wisconsin Board of Regents and is fully accredited by the Higher Learning Commission.

Career-ready skills

Build expertise in Python, machine learning, predictive modeling, data visualization, cloud computing, and more.

Industry connections

Learn from experience faculty and connect with a network of data professionals.

Expert faculty

Online courses are taught by the same instructors and with same rigorous content and standards as on-campus courses. This means you will graduate with the same recognized and respected University of Wisconsin degree as students who attend classes on campus.

Featured courses

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Big Data: High Performance Computing
DS 730 | 3 credits
This course will teach students how to process large datasets efficiently. Students will be introduced to non-relational databases. Students will learn algorithms that allow for the distributed processing of large datasets across clusters. This course will teach students how to process large datasets efficiently. Prerequisite: DS 710 or concurrent enrollment; admission to MS in Data Science. Consent of department. Offered Fall, Spring.
Data Mining and Machine Learning
DS 740 | 3 credits
This course covers data mining and machine learning methods and procedures for diagnostic and predictive analytics. Topics include association rules, clustering algorithms, tools for classification, and ensemble methods. Computer implementation and applications will be emphasized. Prerequisite: DS 705; admission to graduate Data Science Program. Consent of department. Offered Fall, Spring.
Deep Learning
DS 776 | 3 credits
Introduction to the theory and applications of deep learning. The course begins with the study of neural networks and how to train them. Various deep learning architectures are introduced including convolutional neural networks, recurrent neural networks, and transformers. Applications may include image classification, object detection, and natural language processing. Algorithms are implemented in Python using a high-level framework such as Pytorch or TensorFlow. Prerequisite: DS 710, DS 740; admission to MS in Data Science. Offered Fall, Spring.