Program Overview

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Data Science, BS

The Data Science major at the University of WisconsinMadison is designed to equip students with the skills to apply computational, mathematical, and statistical thinking to data-rich problems in a responsible and ethical manner. This includes the ability to manage, process, model, gain meaning and knowledge, and present data.

How to Get in

To declare the Data Science major, students must have:

• Fewer than 86 credits (senior standing)
• Attended a Data Science major declaration event Students may declare in their first semester on campus without an established GPA. However, if courses have been completed at UW-Madison, the following applies:
• At least a 2.000 GPA on coursework that would count in the major
• At least a 2.000 GPA on coursework that would count as upper-level work in the major Or:
• At least a 2.000 GPA in preparatory courses: MATH 96, MATH 112, MATH 113, MATH 114, MATH 171, MATH 211, COMP SCI 200, COMP SCI/E C E 252, COMP SCI 310.

University General Education Requirements

All undergraduate students at the University of Wisconsin-Madison are required to fulfill a minimum set of common university general education requirements to ensure that every graduate acquires the essential core of an undergraduate education. These requirements include:

• BreadthHumanities/Literature/Arts: 6 credits
• BreadthNatural Science: 4 to 6 credits
• BreadthSocial Studies: 3 credits
• Communication Part A & Part B
• Ethnic Studies
• Quantitative Reasoning Part A & Part B

College of Letters & Science Degree Requirements: Bachelor of Science (BS)

Students pursuing a Bachelor of Science degree in the College of Letters & Science must complete all of the requirements below. The College of Letters & Science allows this major to be paired with either the Bachelor of Arts or the Bachelor of Science degree requirements.

Bachelor of Science Degree Requirements

• Mathematics: Complete two courses of 3+ credits at the Intermediate or Advanced level in MATH, COMP SCI, or STAT subjects.
• Language: Complete the third unit of a language other than English.
• L&S Breadth: Complete 12 credits of Humanities, 12 credits of Social Science, and 12 credits of Natural Science.
• Liberal Arts and Science Coursework: Complete at least 108 credits.
• Depth of Intermediate/Advanced Coursework: Complete at least 60 credits at the Intermediate or Advanced level.
• Major: Declare and complete at least one major.
• Total Credits: Complete at least 120 credits.
• UW-Madison Experience: Complete 30 credits in residence, overall, and 30 credits in residence after the 86th credit.
• Quality of Work: 2.000 in all coursework at UWMadison, 2.000 in Intermediate/Advanced level coursework at UWMadison.

Requirements for the Major

Foundational Math Courses

• MATH 221: Calculus and Analytic Geometry 1 (5 credits)
• MATH 222: Calculus and Analytic Geometry 2 (4 credits) Total Credits: 9

Foundational Data Science Courses

• STAT 240: Data Science Modeling I (4 credits)
• STAT 340: Data Science Modeling II (4 credits)
• COMP SCI 220: Data Science Programming I (4 credits)
• COMP SCI 320: Data Science Programming II (4 credits)
• L I S 461: Data and Algorithms: Ethics and Policy (3-4 credits) Total Credits: 19-20

Electives

Students must complete 18 credits of upper-level major electives, including at least one course from each of the following categories: Linear Algebra, Advanced Computing, Statistical Modeling, and Machine Learning, plus additional electives to reach the minimum credits.

Linear Algebra

Choose one from the following:

• MATH 320: Linear Algebra and Differential Equations
• MATH 340: Elementary Matrix and Linear Algebra
• MATH 341: Linear Algebra
• MATH 345: Linear Algebra and Optimization
• MATH 375: Topics in Multi-Variable Calculus and Linear Algebra Total Credits: 3

Advanced Computing

Complete at least one from the following:

• COMP SCI 400: Programming III
• COMP SCI 412: Introduction to Numerical Methods
• COMP SCI/MATH 513: Numerical Linear Algebra
• COMP SCI/MATH 514: Numerical Analysis
• COMP SCI/E C E/I SY E 524: Introduction to Optimization Total Credits: 3

Statistical Modeling

Complete at least one from the following:

• ACT SCI 657: Risk Analytics
• CIV ENGR 516: Hydrologic Data Analysis
• ECON 400: Introduction to Applied Econometrics
• ECON 410: Introductory Econometrics Total Credits: 3

Machine Learning

Complete at least one from the following:

• BSE 405: Artificial Intelligence in Agriculture
• CHEM 361: Machine Learning in Chemistry
• COMP SCI/E C E/M E 532: Matrix Methods in Machine Learning
• COMP SCI/E C E/M E 539: Introduction to Artificial Neural Networks Total Credits: 3

Other Electives

For additional electives, complete up to two courses from the list below or additional courses from the required categories above.

Residence & Quality of Work

• 2.000 GPA in all major courses
• 2.000 GPA in all upper-level work in the major
• 15 credits in the major, taken on the UW-Madison campus

University Degree Requirements

• Total Degree: To receive a bachelor's degree from UWMadison, students must earn a minimum of 120 degree credits.
• Residency: Degree candidates are required to earn a minimum of 30 credits in residence at UWMadison.
• Quality of Work: Undergraduate students must maintain the minimum grade point average specified by the school, college, or academic program to remain in good academic standing.

Learning Outcomes

1. Integrate foundational concepts and tools from mathematics, computer science, and statistics to solve data science problems.
2. Demonstrate competencies with tools and processes necessary for data management and reproducibility.
3. Produce meaning from data employing modeling strategies.
4. Demonstrate critical thinking related to data science concepts and methods.
5. Conduct data science activities aware of and according to policy, privacy, security, and ethical considerations.
6. Demonstrate oral, written, and visual communication skills related to data science.

Four-Year Plan

This Four-Year Plan is only one way a student may complete an L&S degree with this major. Many factors can affect student degree planning, including placement scores, credit for transferred courses, credits earned by examination, and individual scholarly interests.

Three-Year Plan

This Sample Three-Year Plan is a tool to assist students and their advisor(s). Students should use it along with their DARS report, the Degree Planner, and Course Search & Enroll tools to make their own three-year plan based on their placement scores, credit for transferred courses and approved examinations, and individual interests.

Advising and Careers

Information on group declaration sessions, individual advising appointments, drop-in advising, and contact information for advisors is available on the department's website.

What do Data Scientists Do?

Data scientists are trained to manage, process, model, gain meaning and knowledge, and present data. These skills can be employed in a wide variety of different sectors of employment. Examples of interests of students include finance, banking, sports analytics, marketing, retail, humanities, psychology, biosciences, healthcare, and consulting.

Resources and Scholarships

Helpful resources can be found at scholarships and the Wisconsin Scholarship Hub. Additional information specific to Data Science students can be found on the major webpage, and opportunities are regularly sent to declared students via the weekly newsletter.