Program Overview
The Data Science major at the University of Wisconsin-Madison equips students with the knowledge and skills to solve data-rich problems using computational, mathematical, and statistical approaches. Graduates are proficient in data management, modeling, interpretation, and presentation, preparing them for a wide range of careers in the rapidly growing data science sector. The program emphasizes a collaborative learning environment and utilizes a variety of teaching methods, including lectures, hands-on laboratories, and group projects. Graduates are highly sought-after in various industries, including finance, marketing, healthcare, and consulting.
Program Outline
Degree Overview:
Program Overview:
The Data Science major at the University of Wisconsin-Madison equips students with the knowledge and skills to solve data-rich problems across diverse fields using computational, mathematical, and statistical approaches. Graduates are proficient in data management, modeling, interpretation, and presentation, preparing them for a wide range of careers in the rapidly growing data science sector.
Objectives:
- Integrate foundational concepts from mathematics, computer science, and statistics to solve data science problems.
- Demonstrate proficiency in data management and reproducibility tools and processes.
- Extract meaning from data through modeling strategies.
- Develop critical thinking skills related to data science concepts and methods.
- Conduct data science activities ethically and responsibly, considering privacy, security, and policy implications.
- Exhibit effective oral, written, and visual communication skills in data science contexts.
Outline:
Program Structure:
- Foundational Courses:
- Foundational Math Courses: Calculus, Linear Algebra
- Foundational Data Science Courses: Data Science Modeling, Data Science Programming
- Electives:
- Machine Learning: Introduction to Machine Learning, Introduction to Artificial Intelligence
- Advanced Computing: Programming, Numerical Methods
- Statistical Modeling: Introductory Econometrics, Introduction to Time Series
- Linear Algebra: Linear Algebra and Differential Equations, Elementary Matrix and Linear Algebra
- Other Electives: Database Management, Medical Image Analysis, Survey Methods
Course Schedule:
- Freshman Year: Communication A, Ethnic Studies, Calculus, Biological Science, Foreign Language
- Sophomore Year: Linear Algebra, Data Science Modeling II, Data Science Programming II, Literature, Physical Science, Humanities
- Junior Year: Data Science elective, Communication B, Machine Learning, Statistical Modeling, Social Science
- Senior Year: Advanced Computing, Data Science electives, Social Science electives
Assessment:
- Courses include traditional exams and problem sets.
- Completion of a data science project.
Teaching:
- The program utilizes a variety of teaching methods, including:
- Lectures
- Hands-on laboratories
- Group projects
- The faculty are experts in data science and related fields, with active research and industry experience.
- The program emphasizes a collaborative learning environment.
Careers:
- Graduates of the Data Science major are highly sought-after in various industries, including:
- Finance and banking
- Sports analytics
- Marketing
- Retail
- Humanities
- Psychology
- Biosciences
- Healthcare
- Consulting
- The Bureau of Labor Statistics projects a 36% job growth outlook for Data Scientists from 2021-31, significantly faster than average.
- Graduates may also pursue advanced data science skills through graduate education.