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Students
Tuition Fee
Start Date
Medium of studying
Duration
Program Facts
Program Details
Degree
Bachelors
Major
Data Analytics | Data Science
Area of study
Information and Communication Technologies
Course Language
English
About Program

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.
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