Major in Data Science

The LSA Data Science program office is located in 323 West Hall. Appointments with Data Science program advisors can be scheduled through the Undergraduate Advising Page. 

The Data Science major in LSA consists of a total of 42 required credit hours, not including pre-requisites or pre-major courses. All courses must be completed with a minimum grade of C. Note that the EECS department limits students to two attempts for EECS 203, EECS 280, and EECS 281.

Data Science Program Guide

Program Prerequisites:

• EECS 183 (4 credits): Introductory programming 
• Math 115, 116, 215 (4 credits each): Calculus 1-3 
• Math 214 or 217 (4 credits): Linear algebra

Program Core:

• EECS 203 (4 credits): Discrete Mathematics. Acceptable alternative: Math 465. 
• EECS 280 (4 credits): Programming and Elementary Data Structures.
• EECS 281 (4 credits): Data Structures and Algorithms. 
• STATS 412 (3 credits): Introduction to Probability and Statistics. (For other accepted ways to fulfill the STATS 412 requirement, please refer to the Undergraduate FAQs) (Request a permission into STATS 412 without enforced prerequisites and/or without meeting reserves.)
• DATASCI 413/STATS 413 (4 credits): Applied Regression Analysis (F16)

Additional Required Courses:

• Machine learning and data mining elective: EECS 445 or DATASCI 415/STATS 415.
• Data management and applications elective: EECS 484 or EECS 485.
• Data science applications elective (3 credits): The current list of courses that meet this requirement is available here.

Advanced Technical Electives:

Eight credits of Advanced Technical Electives for Data Science. A list of the courses that meet this requirement are available here.

Capstone Experience:

A capstone data science course of at least 3 credits must be taken, typically during the senior year. A list of regular courses meeting the capstone requirement is available here. Another way to meet the capstone experience requirement is to take an independent study (EECS 499 or Stat 489). The latter option will normally involve research in a core aspect of data science or research in a domain area making use of data science methods, possibly as part of an honors degree. The independent study may also document an internship experience that involved substantial activities relating to data science. Any path to meeting the capstone requirement other than pre-approved regular courses must be pre-approved by a Data Science advisor. The course grade for an independent study must be based on a final project report documenting the activities undertaken, and the report must be provided to the DS program office.

Students will need to follow the Statistics Department’s Declaration Process which includes using this Canvas link to enroll in the Statistics & Data Science Pre-declaration Tutorial. Completion of the tutorial will unlock the declaration request form.

To declare the major, students will have completed EECS 183 and MATH 115, MATH 116 and MATH 215 with grades of C or higher.

Students must complete the linear algebra prerequisite requirement, but can do this after declaring.

**A Data Science and a Computer Science double major is permitted in LSA. Students are required to complete 14 credits in their Computer Science major that are not double counted with the Data Science major. Students planning this double major should meet with an advisor to plan their curriculum.**

Most combinations of a Data Science major in LSA with other majors or minors is permitted, consistent with the LSA rules, except for the following combinations:

• Data Science major with a Statistics or Applied Statistics minor 
  

• Data Science major with a Computer Science minor