ls-datascience

Students in the Data Science major will be able to apply computational, mathematical, and statistical thinking to data-rich problems in a wide variety of fields in a responsible and ethical manner. This includes the ability to manage, process, model, gain meaning and knowledge, and present data. Data Science is one of the fastest growing career sectors in Wisconsin and across the nation.

By its very nature, the field of data science is one that teaches novel and cutting-edge ways to engage in the “continual sifting and winnowing by which alone the truth can be found.”

To declare the data science major, student should set up an appointment with a data science major advisor prior to attaining senior standing (86 credits).  There are no specific courses that must be completed before declaration.

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. This core establishes a foundation for living a productive life, being a citizen of the world, appreciating aesthetic values, and engaging in lifelong learning in a continually changing world. Various schools and colleges will have requirements in addition to the requirements listed below. Consult your advisor for assistance, as needed. For additional information, see the university Undergraduate General Education Requirements section of the Guide.

General Education
  • Breadth—Humanities/Literature/Arts: 6 credits
  • Breadth—Natural Science: 4 to 6 credits, consisting of one 4- or 5-credit course with a laboratory component; or two courses providing a total of 6 credits
  • Breadth—Social Studies: 3 credits
  • Communication Part A & Part B *
  • Ethnic Studies *
  • Quantitative Reasoning Part A & Part B *

* The mortarboard symbol appears before the title of any course that fulfills one of the Communication Part A or Part B, Ethnic Studies, or Quantitative Reasoning Part A or Part B requirements.

College of Letters & Science Breadth and Degree Requirements: Bachelor of Science (B.S.)

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 a bachelor of arts or a bachelor of science curriculum. View a comparison of the degree requirements here.

Bachelor of Science DEGREE REQUIREMENTS

Mathematics Two (2) 3+ credits of intermediate/advanced level MATH, COMP SCI, STAT
Limit one each: COMP SCI, STAT
Foreign Language Complete the third unit of a foreign language
Note: A unit is one year of high school work or one semester/term of college work.
L&S Breadth
  • Humanities, 12 credits: 6 of the 12 credits must be in literature
  • Social Sciences, 12 credits
  • Natural Sciences, 12 credits: must include 6 credits in biological science; and must include 6 credits in physical science
Liberal Arts and Science Coursework 108 credits
Depth of Intermediate/Advanced work 60 intermediate or advanced credits
Major Declare and complete at least one (1) major
Total Credits 120 credits
UW-Madison Experience 30 credits in residence, overall
30 credits in residence after the 86th credit
Minimum GPAs 2.000 in all coursework at UW–Madison
2.000 in intermediate/advanced coursework at UW–Madison

Non–L&S Students PURSUING AN L&S MAJOR

Non–L&S students who have permission from their school/college to pursue an additional major within L&S only need to fulfill the major requirements and do not need to complete the L&S breadth and degree requirements above.  Please note that the following special degree programs are not considered majors so are not available to non-L&S-degree-seeking candidates:  

  • Applied Mathematics, Engineering and Physics (Bachelor of Science–Applied Mathematics, Engineering and Physics)
  • Journalism (Bachelor of Arts–Journalism; Bachelor of Science–Journalism)
  • Music (Bachelor of Music)
  • Social Work (Bachelor of Social Work)

Requirements for the Major

Foundational Math Courses 1
MATH 221 Calculus and Analytic Geometry 15
or MATH 217 Calculus with Algebra and Trigonometry II
or MATH 275 Topics in Calculus I
MATH 222 Calculus and Analytic Geometry 24
or MATH 276 Topics in Calculus II
Foundational Data Science Courses
STAT 240 Introduction to Data Modeling I4
STAT 340 Introduction to Data Modeling II4
COMP SCI 220 Data Programming I4
COMP SCI 320 Data Programming II4
L I S 461 Data and Algorithms: Ethics and Policy3-4
Electives18
Students must take at least one course from each of the four following categories and then additional electives to reach the minimum credits. Additional courses taken within each category may count towards other electives.
Machine Learning3
Select one of the following:
Matrix Methods in Machine Learning 2
Introduction to Artificial Neural Networks
Introduction to Artificial Intelligence
Mathematical Methods in Data Science
Introduction to Machine Learning and Statistical Pattern Classification
Introduction to Deep Learning and Generative Models
Advanced Computing3
Select one of the following:
Programming III
Introduction to Numerical Methods
Introduction to Computational Statistics
Numerical Linear Algebra
Numerical Analysis
Introduction to Optimization
Database Management Systems: Design and Implementation
Advanced Geocomputing and Geospatial Big Data Analytics
Geospatial Database Design and Development
Statistical Modeling3
Select one of the following:
Introduction to Applied Econometrics
Introductory Econometrics
Introduction to Probability and Mathematical Statistics I
Introduction to Probability and Mathematical Statistics II
Introduction to Theory and Methods of Mathematical Statistics I
Introduction to Theory and Methods of Mathematical Statistics II
Introduction to Time Series
Introductory Nonparametric Statistics
Applied Categorical Data Analysis
Statistical Experimental Design
Introduction to the Theory of Probability
Classification and Regression Trees
Applied Multivariate Analysis
Financial Statistics
Probability Theory
Introduction to Stochastic Processes
An Introduction to Brownian Motion and Stochastic Calculus
Linear Algebra 20-3
Select one from the following:
Linear Algebra and Differential Equations
Elementary Matrix and Linear Algebra
Linear Algebra
Topics in Multi-Variable Calculus and Linear Algebra
Matrix Methods in Machine Learning 2
Other Electives6-9
For additional electives select from the courses listed below or additional courses from the required categories above:
Signals, Information, and Computation
Fundamentals of Data Analytics for Economists
Graphic Design in Cartography
Interactive Cartography & Geovisualization
Operations Research-Deterministic Modeling
Fundamentals of Industrial Data Analytics
Inspection, Quality Control and Reliability
Introduction to Quality Engineering
Information Sensing and Analysis for Manufacturing Processes
Introduction to Combinatorial Optimization
Linear Optimization
Image Processing
Computer Graphics
Medical Image Analysis
Introduction to Bioinformatics
Introduction to Algorithms

Residence & Quality of Work

  • 2.000 GPA in all major courses
  • 2.000 GPA in all upper level work in the major2
  • 15 credits in the major, taken on the UW-Madison campus

University Degree Requirements

Total Degree To receive a bachelor's degree from UW–Madison, students must earn a minimum of 120 degree credits. The requirements for some programs may exceed 120 degree credits. Students should consult with their college or department advisor for information on specific credit requirements.
Residency Degree candidates are required to earn a minimum of 30 credits in residence at UW–Madison. "In residence" means on the UW–Madison campus with an undergraduate degree classification. “In residence” credit also includes UW–Madison courses offered in distance or online formats and credits earned in UW–Madison Study Abroad/Study Away programs.
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. Students whose academic performance drops below these minimum thresholds will be placed on academic probation.
  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.

Sample Four-Year Plan

This Sample Four-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 four-year plan based on their placement scores, credit for transferred courses and approved examinations, and individual interests. As students become involved in athletics, honors, research, student organizations, study abroad, volunteer experiences, and/or work, they might adjust the order of their courses to accommodate these experiences. Students will likely revise their own four-year plan several times during college.

Sample Four-Year Plan

This Sample Four-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 four-year plan based on their placement scores, credit for transferred courses and approved examinations, and individual interests. As students become involved in athletics, honors, research, student organizations, study abroad, volunteer experiences, and/or work, they might adjust the order of their courses to accommodate these experiences. Students will likely revise their own four-year plan several times during college.

Freshman
FallCreditsSpringCredits
COMP SCI 2204COMP SCI 3204
Communication A3MATH 2215
Biological Science Breadth3Ethnic Studies3
Foreign Language (if needed)4Foreign Language (if needed)4
 14 16
Sophomore
FallCreditsSpringCredits
MATH 2224STAT 3404
STAT 2404Linear Algebra course3
Literature Breadth3Humanities Breadth3
Physical Science Breadth3Literature Breadth3
INTER-LS 2101Social Science Breadth3
 15 16
Junior
FallCreditsSpringCredits
L I S 461 (enroll in Communication B section)3-4Statistical Modeling course3
Machine Learning course3Physical Science Breadth3
Biological Science Breadth3Social Science Breadth3
Social Science Breadth3Electives6
Elective3 
 16 15
Senior
FallCreditsSpringCredits
Advanced Computing course3Data Science elective3
Data Science elective3Electives10
Social Science Breadth3 
Electives6 
 15 13
Total Credits 120

Looking for Data Science advising?

Students who are interested in data science academic advising should check out the advising information on our website or send an email to dsmajor@stat.wisc.edu.

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 our students include finance, banking, sports analytics, marketing, retail, humanities, psychology, biosciences, healthcare, and consulting, just to name a few.  Students are encouraged to combine data science with majors, certificates, and courses from differing areas to best be able to apply their data science in the area of their choosing.

Data science is one of the fastest growing area of jobs in the U.S. and in Wisconsin. All of the major job search engines regularly list thousands of jobs, for example, in 2018 Data Scientist was the #1 job on the web site Glassdoor with over 25,000 jobs, Monster.com listed over 12,000 jobs in data science nationally, and Indeed.com had over 1,000 jobs for data analysts just in the state of Wisconsin.

Additionally, the Occupational Outlook Handbook (OOH) from the Bureau of Labor Statistics shows the job growth outlook from 2016-26 for Mathematicians and Statisticians to be 33% (much faster than average) and for Computer and Information Research Scientists to be 19% (much faster than average). 

Some students may want to continue to develop additional advanced data science skills through graduate education.

L&S career resources

SuccessWorks at the College of Letters & Science helps students leverage the academic skills learned in their major, certificates, and liberal arts degree; explore and try out different career paths; participate in internships; prepare for the job search and/or graduate school applications; and network with professionals in the field (alumni and employers). In short, SuccessWorks helps students in the College of Letters & Science discover themselves, find opportunities, and develop the skills they need for success after graduation.

SuccessWorks can also assist students in career advising, résumé and cover letter writing, networking opportunities, and interview skills, as well as course offerings for undergraduates to begin their career exploration early in their undergraduate career. 

Students should set up their profiles in Handshake to take care of everything they need to explore career events, manage their campus interviews, and apply to jobs and internships from 200,000+ employers around the country.

Advising Staff

Sara Rodock

Data Science Major Program Committee

  • Michael Ferris (Computer Sciences)
  • Bret Larget, Program Director (Statistics)
  • Sebastien Roch (Mathematics)
  • Alan Rubel (iSchool)

Visit the Wisconsin Scholarship Hub (WiSH) to find UW–Madison scholarships and apply online.