Data Science B.S.
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.
In order to continue as a major in Data Science in CEMS, a student must achieve a 2.00 cumulative grade-point average at the end of the semester in which 60 cumulative credits have been attempted. No more than three repeated course enrollments are allowed during this 60-credit period. In the case of transfer students, applicable transfer credits will be included in determining the 60 credits, but grades in these courses will not be included in the grade-point average.
Students who receive a cumulative or semester grade-point average of less than 2.00 will be placed on trial. Students who have failed half their course credits for any semester, or who have had two successive semester averages below 2.00, or three successive semesters in which their cumulative grade-point average falls below 2.00, are eligible for dismissal.
To receive a degree, students must have a minimum cumulative average of 2.00. Students must complete 30 of the last 45 hours of credit in residence at UVM as matriculated students in the College of Engineering and Mathematical Sciences.
The Curriculum for the B.S. in Data Science
|CS 064||Discrete Structures||3|
|or MATH 052||Fundamentals of Mathematics|
|STAT 151||Applied Probability||3|
|or STAT 251||Probability Theory|
|or CS 128||Probability Models & Inference|
|CS 008||Intro to Web Site Development||3|
|CS 021||Computer Programming I||3|
|CS 110||Intermediate Programming||4|
|CS 124||Data Structures & Algorithms||3|
|CS 204||Database Systems||3|
|100-Level (or above) CS Elective 1||3|
|200-Level (or above) CS Elective 1||3|
|STAT 087||Introduction to Data Science||3|
|STAT 141||Basic Statistical Methods||3|
|or STAT 143||Statistics for Engineering|
|or STAT 211||Statistical Methods I|
|STAT 221||Statistical Methods II||3|
|STAT 201||Stat Computing & Data Analysis||3|
|STAT 223||Applied Multivariate Analysis||3|
|STAT 229||Survival/Logistic Regression||3|
|STAT 287||Data Science I||3|
|MATH 021||Calculus I||4|
|MATH 022||Calculus II||4|
|MATH 122||Applied Linear Algebra||3|
|or MATH 124||Linear Algebra|
|Choose 3 MATH 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|
|Database Design for the Web|
|Algorithm Design & Analysis|
|Programming for Bioinformatics|
|Modeling Complex Systems 3|
|Data Mining 3|
|Evolutionary Computation 3|
|Basic Combinatorial Theory|
|Mathematical Models & Analysis|
|Intro to Numerical Analysis|
|Principles of Complex Systems 3|
|Complex Networks 3|
|Statistics for Business|
|Stats for Quality&Productivity|
|Applied Regression Analysis|
|Categorical Data Analysis|
|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
|University Requirements 4||12|
|Foundational Writing & Information Literacy||3|
|Diversity Category 1||3|
|Diversity Category 1 or 2||3|
|Free electives 5||19|
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.
See University Requirements section of this catalogue for additional information.
Students are encouraged to use free elective credits to complete a minor in an area of application (e.g., biology, social sciences).
Complex Systems and Data Science AMP
Complex Systems and Data Science M.S.
See the online Graduate Catalogue for more information