The rapidly expanding collection and use of data is driving transformations across broad segments of industry, science, and society. These changes have sparked great demand for individuals with skills in managing and analyzing complex data sets. Such skills are interdisciplinary, involving ideas typically associated with computing, information processing, mathematics, and statistics as well as the development of new methodologies spanning these fields. Our major in Data Science (offered jointly with the Department of Mathematics and SCI) offers a program specifically geared to training students to participate in this data revolution.
This undergraduate major allows students to gain critical skill sets that span key areas of mathematics, computing, and statistics, with foundational training providing literacy in four areas (data, algorithmic, mathematical, and statistical) that every student needs to master data science. Students will develop expertise that connects theory to the solution of real-world problems and be able to specialize their studies towards a more specific career focuses. Completing this major will prepare students to work as a data science professional or to pursue graduate study in a direction involving data in a significant way.
Choosing between the Data Science and other Statistics Majors
Students who graduate with any of the Statistics majors or the Data Science major will be well qualified for positions in data science. The Data Science major is designed for students whose main passion is working with data, including mathematical, statistical, and computing aspects. The other Statistics majors are designed for students whose primary interest is in statistics or with an emphasis on economics. It is also quite possible to complete a double major in Data Science and one of the Statistics majors.
Major Requirements
For the most current course requirements, please refer to the Dietrich School of Arts & Sciences Undergraduate Studies Department's program requirements sheet for the Data Science major. The information displayed below is intended only to serve as a reference.
Foundation
CMPINF 1061/STAT 1060 Data Science Foundations
CMPINF 0401 Intermediate Programming
CS 0445 Algorithms and Data Structures 1
MATH 0220 Calculus 1
MATH 0230 Calculus 2
MATH 0280/MATH 1180 Intro. to Matrices/Linear Algebra
MATH 0480/CS 0441 Applied Discrete Mathematics
STAT 1151/STAT 1631 Intro. to/Intermediate Probability
STAT 1152/STAT 1632 Intro. to/Intermediate Mathematical Statistics
Expertise
CS 0590 Social Implications of Computing Technology
CS 1501 Algorithms and Data Structures 2
CS 1656 Introduction to Data Science
CS 1675 Introduction to Machine Learning or STAT 1361 Statistical Learning and Data Science
MATH 1101 Introduction to Optimization
STAT 1261 Principles of Data Science
Specialization
Computer Systems
Data Analytics
Data Science in Context
Modeling
Capstone
Students must complete one of the following 3 courses:
CMPINF 1981 Project Studio
MATH 1103 BIG Problems
STAT 1961 Data Science in Action