The Data Science program will not accept majors until Fall 2022.
4118B Mathematical Sciences; 530- 752-1053; Statistics
The B.S. Major
Data Science combines computational, mathematical and statistical reasoning to draw conclusions based on data. Data science techniques and methods can be applied to problems from virtually any discipline; for example, in agricultural and environmental sciences, biological sciences, engineering, medical sciences and social sciences.
Data Science majors receive a Bachelor of Science degree. The program requires both theoretical and applied course work to underscore the strong interdependence of technical foundations in computer science, engineering, mathematics and statistics, and their applications to any field of inquiry relying on quantitative data analysis. The B.S. degree program has one track, the Foundations track.
B.S. in Data Science-Foundations Track emphasizes the underlying computer science, engineering, mathematics and statistics methodology and theory, and is especially recommended as preparation for graduate study in data science or related fields.
Inferential and computational techniques are used in many fields, including the agricultural and environmental sciences, biological sciences, social sciences, and health sciences, business, and engineering. The wide applicability of data science is reflected in the strong demand for graduates with data science training in both the public and private sectors. Employment opportunities include careers in data & policy analysis in government & industry, tech industry, insurance & healthcare industry, engineering, public health, biological & pharmaceutical research, law, and education. Students with an undergraduate degree in data science may enter advanced studies in data science, computer science, applied mathematics, statistics, economics, finance, psychology, medicine, business management & analytics, and other professional school programs.
The Data Science major will not accept majors until Fall 2022. To learn more about other majors in the Department of Statistics that are currently accepting students, please consult Statistics Undergraduate Advising.
|Preparatory Subject Matter|
|Computer Science Engineering|
|ECS 017||Data, Logic, & Computing||4|
|ECS 032A||Introduction to Programming||4|
|ECS 032B||Introduction to Data Structures||4|
|MAT 022A||Linear Algebra||3|
|STA 035A||Statistical Data Science I||4|
|STA 035B||Statistical Data Science II||4|
|STA 035C||Statistical Data Science III||4|
|All prerequisites for preparatory material are themselves part of the preparatory material.|
|Preparatory Subject Matter Subtotal||39|
|Depth Subject Matter|
|Computer Science Engineering|
|ECS 116||Databases for Non-Majors||4|
|ECS 117||Algorithms for Data Science (Pending Approval)||4|
|ECS 119||(Pending Approval)||4|
|ECS 130||Scientific Computation||4|
|or MAT 167||Applied Linear Algebra|
|Mathematics for Data Analytics & Decision Making|
|Statistical Learning I|
|or STA 131A||Introduction to Probability Theory|
|STA 108||Applied Statistical Methods: Regression Analysis||4|
|STA 141A||Fundamentals of Statistical Data Science||4|
|Science & Technology Studies|
|STS 101||Data & Society||4|
|Three elective courses in a related discipline.||12|
|Depth Subject Matter Subtotal||52|