Data Science University of Wisconsin Milwaukee

Overview

The Data Science programme at the University of Wisconsin Milwaukee provides a comprehensive foundation for students passionate about mathematics and computing. This degree equips graduates with the analytical tools required to interpret vast datasets and drive informed decision-making across various global industries.

Students learn to apply the scientific method to validate hypotheses and develop sophisticated computer algorithms. The curriculum bridges the gap between data engineering and analysis, ensuring graduates understand both technical infrastructure and practical application. This balanced approach prepares individuals to solve real-world problems in government, healthcare, and business sectors.

Why Data Science at University of Wisconsin Milwaukee?

The university is situated in a prime location for aspiring data professionals, with Milwaukee serving as a hub for major corporations. Renowned organisations such as Harley-Davidson, Rockwell Automation, and Johnson Controls frequently recruit from the campus. This proximity offers students a distinct advantage when seeking professional connections and local industry insights.

Undergraduates can also join the dedicated Data Science Club, which hosts weekly presentations to enhance peer learning and networking. The institution provides a robust support system, including success coaches and academic advisors, to help students define their career goals. Furthermore, the university offers access to the Panther Scholarship Portal to assist with educational funding.

Tuition Fee Breakdown

• International fee: USD 24368 per year
• National fee: USD 24368 per year
• Local fee: USD 11768 per year

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

Syllabus

The curriculum requires a minimum of 120 credits, including core subjects and a mandatory capstone or internship. Modules may include:

• Computer Programming
• Intermediate Computer Programming
• Statistical Analysis
• Statistical Computing and Data Science
• Mathematical Statistics
• Regression Analysis
• Computational Statistics
• Multivariate Statistical Analysis
• Discrete Information Structures
• Data Structures and Algorithms
• Artificial Intelligence
• Machine Learning and Applications
• Data Mining
• Database Systems
• Writing, Speaking, and Technoscience in the 21st Century

Careers with Data Science

Graduates are well-positioned for roles in one of the fastest-growing professional sectors, with high demand for skills in machine learning and artificial intelligence. The programme prepares students for diverse career paths, including roles as data scientists, data analysts, and machine learning technicians. Many graduates also find success as artificial intelligence programmers.

Employment opportunities exist across a wide range of industries, from retail giants like Amazon to healthcare organisations and government agencies. While entry-level positions are available with a bachelor's degree, the curriculum provides a strong foundation for those wishing to pursue advanced master's level study. The versatility of the degree ensures graduates can adapt to various regional and industrial requirements.