The Computational Data Science Degree develops strong interdisciplinary skills in mathematics, statistics, computer science and big data processing. Create algorithms, write code and scripts to solve problems beyond the basic use of existing tools in support of an industrial, enterprise-level big data pipeline. The mix of competencies and experiences required for Data Science differs significantly from those developed in the individual degree programs in the four areas mentioned above. Gain real-world experience as a springboard to working in industry as a Data Scientist or to pursue a graduate degree.

Total Program Credits: 121

General Education Requirements:			35 Credits
	ENGL 1010	Introduction to Academic Writing CC	3
or	ENGH 1005	Literacies and Composition Across Contexts CC (5)
	ENGL 2010	Intermediate Academic Writing CC	3
	MATH 1210	Calculus I QL	4
American Institutions: Complete one of the following:			3
	HIST 1700	American Civilization AS (3)
	HIST 1740	US Economic History AS (3)
	HIST 2700	US History to 1877 AS (3)
and	HIST 2710	US History since 1877 AS (3)
	POLS 1000	American Heritage SS (3)
	POLS 1100	American National Government AS (3)
Complete the following:
	PHIL 2050	Ethics and Values IH	3
	HLTH 1100	Personal Health and Wellness TE (2)
or	EXSC 1097	Fitness for Life TE	2
Distribution Courses:
	COMM 1020	Public Speaking HH *	3
	COMM 2110	Interpersonal Communication SS *	3
	Biology (choose from list)		3
	Fine Arts Distribution (choose from list)		3
	PHYS 2210	Physics for Scientists and Engineers I PP *	4
and	PHYS 2215	Physics for Scientists and Engineers I Lab*	1
Discipline Requirements:			74 Credits
Complete one of the following GE course/lab combinations:			5
	BIOL 1610	College Biology I BB (4)
and	BIOL 1615	College Biology I Laboratory (1)
or	CHEM 1210	Principles of Chemistry I PP (4)
and	CHEM 1215	Principles of Chemistry I Laboratory (1)
or	PHYS 2020	College Physics II PP (4)
and	PHYS 2025	College Physics II Lab (1)
or	PHYS 2220	Physics for Scientists and Engineers II PP (4)
and	PHYS 2225	Physics for Scientists and Engineers II Lab (1)
Minimum grade of C- required in these courses.
Computer Science
	CS 1400	Fundamentals of Programming	3
	CS 1410	Object-Oriented Programming	3
	CS 2420	Introduction to Algorithms and Data Structures	3
	CS 2300	Discrete Mathematical Structures I	3
	CS 2700	Causal Inference	3
	CS 3100	Data Privacy and Security	3
	CS 3520	Database Theory	3
	CS 3270	Python Software Development	3
	CS 3320	Numerical Software Development	3
	CS 3530	Data Management For Data Sciences	3
	CS 3800	Data Science Through Statistical Reasoning	3
	CS 3810	Applied Data Science	3
	CS 3820	Visualization Analytics for Data Science	3
	CS 305G	Global Social and Ethical Issues in Computing	3
	CS 4700	Machine Learning I	3
	CS 4710	Machine Learning II	3
	CS 4800	Data Science Capstone	3
Mathematics
	MATH 1220	Calculus II	4
	MATH 2210	Calculus III	4
	MATH 2270	Linear Algebra	3
Statistics
	STAT 2050	Introduction to Statistical Methods	4
	ECE 3710	Applied Probability and Statistics for Engineers and Scientists	3
Elective Requirements:			12 Credits
Complete 12 credits from any of the following (A minimum grade of C- is required):			12
	4 courses from another discipline, at least 6 hours of which must be 3000 level or higher. Requires department head approval.
	Any CS 3000 or 4000 level course not already required

Graduation Requirements:

1. Completion of a minimum of 120 semester credits, with a minimum of 40 upper-division credits.
2. Overall grade point average of 2.0 or above.
3. Must have a minimum grade of C- with a combined GPA of 2.5 or higher in all discipline requirements and the General Education requirements that are marked with an *.
4. Residency hours -- minimum of 30 credit hours through course attendance at UVU. 10 of these hours must be within the last 45 hours earned. At least 12 of the credit hours earned in residence must be in approved Computational Data Science (CDS) courses.
5. All transfer credit must be approved in writing by UVU.
6. No more than 80 semester hours and no more than 20 hours in CDS type courses of transfer credit from a two-year college.
7. No more than 30 semester hours may be earned through independent study and/or extension classes.
8. Successful completion of at least one Global/Intercultural course. CS 305G satisfies this requirement.