Undergraduate Degree

The Bachelor of Science degree in Computational Data Science focuses on the computational foundations of data science, providing an in-depth understanding of the algorithms and data structures for storing, manipulating, visualizing, and learning from large data sets. Students in the program have unique access to a wide range of fundamental computer science courses in topics ranging from mobile application and web development to theory of computation and fundamental algorithms. Students can tailor their degree to their unique interests and requirements, with an emphasis on computational foundations.

Requirements for the Bachelor of Science Degree in Computational Data Science

1. The University requirements for bachelor's degrees as described in the Undergraduate Education section of this catalog; 120 credits, including general elective credits, are required for the Bachelor of Science degree in Computational Data Science.
   
   The University's Tier II writing requirement for the Computational Data Science major is met by completing Computational Mathematics, Science and Engineering 495, referenced in item 3. b. below.
   
   Students who are enrolled in the College of Engineering may complete the alternative track to Integrative Studies in Biological and Physical Sciences that is described in item 1. under the heading Graduation Requirements for All Majors in the College statement.
2. The requirements of the College of Engineering for the Bachelor of Science degree.
   
   The credits earned in certain courses referenced in requirement 3. below may be counted toward College requirements as appropriate.
3. The following requirements for the major:

   a.	Bioscience (4 to 6 credits)
   	(1)	One of the following courses:
   		BS	161	Cell and Molecular Biology					3
   		ENT	205	Pests, Society and Environment					3
   		IBIO	150	Integrating Biology: From DNA to Populations					3
   		MMG	141	Introductory Human Genetics					3
   		MMG	201	Fundamentals of Microbiology					3
   		PLB	105	Plant Biology					3
   		PSL	250	Introductory Physiology					4
   	(2)	One of the following courses:
   		BS	171	Cell and Molecular Biology Laboratory					2
   		CEM	161	Chemistry Laboratory I					1
   		CEM	162	Chemistry Laboratory II					1
   		PHY	191	Physics Laboratory for Scientists, I					1
   		PHY	192	Physics Laboratory for Scientists, II					1
   		PLB	106	Plant Biology Laboratory					1
   b.	All of the following courses (44 credits):
   	CMSE	201	Introduction to Computational Modeling and Data Analysis						4
   	CMSE	381	Fundamentals of Data Science Methods						4
   	CMSE	382	Optimization Methods in Data Science						4
   	CMSE	495	Experiential Learning in Data Science (W)						4
   	CSE	232	Introduction to Programming II						4
   	CSE	300	Social, Ethical, and Professional Issues in Computer Science						1
   	CSE	331	Algorithms and Data Structures						3
   	CSE	404	Introduction to Machine Learning						3
   	CSE	482	Big Data Analysis						3
   	CSE	480	Database Systems						3
   	MTH	314	Matrix Algebra with Computational Applications						3
   	STT	180	Introduction to Data Science						4
   	STT	380	Probability and Statistics for Data Science						4
   c.	Two courses selected from the following (6 credits):
   	CSE	402	Biometrics and Pattern Recognition						3
   	CSE	415	Introduction to Parallel Computing						3
   	CSE	431	Algorithm Engineering						3
   	CSE	440	Introduction to Artificial Intelligence						3
   	Computer Science and Engineering 415 and Computational Science, Mathematics and Engineering 401 may not be used to fulfill both requirements c. and d.
   d.	Two courses selected from the following (6 credits):
   	CMSE	401	Methods for Parallel Computing						4
   	CMSE	402	Data Visualization Principles and Techniques						3
   	CSE	402	Biometrics and Pattern Recognition						3
   	CSE	415	Introduction to Parallel Computing						3
   	CSE	431	Algorithm Engineering						3
   	CSE	440	Introduction to Artificial Intelligence						3
   	CSE	471	Media Processing and Multimedia Computing						3
   	CSE	472	Computer Graphics						3
   	MTH	451	Numerical Analysis I						3
   	MTH	468	Predictive Analytics						3
   	STT	464	Statistics for Biologists						3
   	STT	465	Bayesian Statistical Methods						3
   	Computer Science and Engineering 415 and Computational Science, Mathematics and Engineering 401 may not be used to fulfill both requirements c. and d.