Data Science B.S.
Data Science Major
The study and applications of Data Science impacts our lives in myriad ways every moment of every day. Often times we are unaware of the role this important field plays in our daily routines. We have data scientists to thank as we read the latest news on our social media feed of choice, or watch a movie suggested by our go-to streaming app. Even the food we eat has likely been guided by the study of big data. Researchers are working hand-in-hand with farms of all sizes to help analyze data which in turn can identify and reduce areas of inefficiency and waste, and bring food to your table in a faster, safer, and more cost-effective way.
The curriculum of the Bachelor of Science with a major in Data Science combines courses from the disciplines of Statistics, Mathematics, and Computer Science to prepare students for careers in Big Data Science & Analytics: rapidly growing fields with huge unmet demand. The unique interdisciplinary educational experience allows students the opportunity to acquire the broad base of knowledge and skills that employers are seeking.
Students pursuing the Bachelor of Science degree with a major in Data Science are subject to the Academic Standards in CEMS outlined in this catalogue.
The Curriculum for the B.S. in Data Science
A minimum of 120 credits is required. Students must satisfy all University requirements.
|Core (6 credits):|
|CS 064||QR: Discrete Structures||3|
|or MATH 052||QR:Fundamentals of Mathematics|
|STAT 151||QR: Applied Probability||3|
|or STAT 251||QR: Probability Theory|
|or CS 128||QR:Probability Models & Infrnc|
|Computer Science Core (22 credits):|
|CS 008||QR: Intro to Web Site Dev||3|
|CS 021||QR: Computer Programming I||3|
|CS 110||QR: Intermediate Programming||4|
|CS 124||QR: Data Struc & Algorithms||3|
|CS 204||QR: Database Systems||3|
|CS 224||QR:Algorithm Design & Analysis||3|
|100-Level (or above) CS Elective 1||3|
|Statistics Core (21 credits):|
|STAT 087||QR: Intro to Data Science||3|
|STAT 141||QR:Basic Statistical Methods 1||3|
|or STAT 143||QR: Statistics for Engineering|
|or STAT 211||QR: Statistical Methods I|
|STAT 221||QR: Statistical Methods II||3|
|STAT 201||QR:Stat Computing&Data Anlysis||3|
|STAT 223||QR:Appld Multivariate Analysis||3|
|STAT 229||QR:Survivl/Logistic Regression||3|
|STAT/CS 287||QR: Data Science I||3|
|Mathematics Core (20 credits):|
|MATH 021||QR: Calculus I||4|
|MATH 022||QR: Calculus II||4|
|MATH 122||QR: Applied Linear Algebra||3|
|or MATH 124||QR: Linear Algebra|
|Choose 9 credits in Mathematics electives at the 100-Level (or above) 1||9|
|Choose 12 Credits in Data Science (DS) electives selected from the list of approved courses (see below) in MATH/STAT/CS/CSYS/NR, with at least 9 of these credits at the 200-level (or above): 2||12|
|QR: Advanced Programming|
|QR: Database Design for Web|
|QR: Cybersecurity Principles|
|QR: Software Engineering|
|QR:Algorithm Design & Analysis|
|QR: Human-Computer Interaction|
|QR: Programming for Bioinform|
|QR: Artificial Intelligence|
|QR: Machine Learning|
|QR: Neural Computation|
|Modeling Complex Systems 3|
|Data Mining 3|
|Evolutionary Computation 3|
|QR: Calculus III|
|QR: Basic Combinatorial Theory|
|QR:Intro to Numerical Analysis|
|Principles of Complex Systems 3|
|Complex Networks 3|
|QR:Basic Statistical Methods 2|
|QR:Stats for Qualty&Productvty|
|QR:Applied Regression Analysis|
|QR: Experimental Design|
|QR: Survey Sampling|
|QR: Categorical Data Analysis|
|QR: Statistical Inference|
|QR: Statistical Learning|
|Bayesian Statistics 3|
|Data Science II 3|
|Intro to Geog Info Systems|
|Appld Artificial Neural Ntwrks 3|
|Applied Geostatistics 3|
|Choose one 2-course Natural Science (w/ lab) sequence:||8|
|Principles of Biology|
and Principles of Biology
|General Chemistry 1|
and General Chemistry 2
|Fundamentals of Physics I|
and Fundamentals of Physics II
Students should select appropriate courses from list of approved Data Science (DS) electives. Alternative courses may be approved by the DS Curriculum Committee.
Additional courses, including special topics courses, may be granted approval if appropriate (consult advisor).
Undergraduate students require instructor permission to enroll in 300-level courses.
Complex Systems and Data Science AMP
Complex Systems and Data Science M.S.
Complex Systems and Data Science Ph.D.
See the online Graduate Catalogue for more information