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Computational Data Science, B.S.

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Requirements

The BS in Computational Data Science develops strong interdisciplinary skills in mathematics, statistics, computer science, and big data processing. The program teaches how to create algorithms and 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. Students will 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 3
or ENGH 1005 Literacies and Composition Across Contexts (5)   
  ENGL 2010 Intermediate Writing Academic Writing and Research 3
  MATH 1210 Calculus I  4
American Institutions: Complete one of the following:  3
  HIST 1700 American Civilization  (3)  
  HIST 1740 US Economic History  (3)  
  HIST 2700 US History to 1877  (3)  
and HIST 2710 US History since 1877  (3)  
  POLS 1000 American Heritage  (3)  
  POLS 1100 American National Government  (3)  
Complete the following:   
  PHIL 2050 Ethics and Values 3
  HLTH 1100 Personal Health and Wellness (2)  
or EXSC 1097 Fitness for Life 2
Distribution Courses:   
  COMM 1020 Public Speaking * 3
  COMM 2110 Interpersonal Communication * 3
  Biology (choose from list)  3
  Fine Arts Distribution (choose from list)  3
  PHYS 2210 Physics for Scientists and Engineers I * 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 (4)  
and BIOL 1615 College Biology I Laboratory (1)  
 or CHEM 1210 Principles of Chemistry I (4)  
and CHEM 1215 Principles of Chemistry I Laboratory (1)  
or PHYS 2020 College Physics II (4)  
and PHYS 2025 College Physics II Lab (1)  
or PHYS 2220 Physics for Scientists and Engineers II (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 2300 Discrete Mathematical Structures I 3
  CS 2420 Introduction to Algorithms and Data Structures 3
  CS 2700 Causal Inference 3
  CS 305G Global Social and Ethical Issues in Computing 3
  CS 3100 Data Privacy and Security 3
  CS 3270 Python Software Development 3
  CS 3320 Numerical Software Development 3
  CS 3520 Database Theory 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 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  
  ECE 3710 Applied Probability and Statistics for Engineers and Scientists 3
  STAT 2050 Introduction to Statistical Methods 4
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 thatare 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.

Graduation Plan

This graduation plan is a sample plan and is intended to be a guide. Your specific plan may differ based on your Math and English placement and/or transfer credits applied. You are encouraged to meet with an advisor and set up an individualized graduation plan in Wolverine Track.

Milestone courses (pre-requisites for a course in one of the subsequent semesters) are marked in red and Italicized.

Semester 1 Course Title Credit Hours
CS 1400 Fundamentals of Programming 3
ENGL 1010 or ENGH 1005

Introduction to Academic Writing or Literacies and Composition Across Contexts

3
MATH 1210 Calculus I 4
STAT 2050 Introduction to Statistical Methods 4
  Semester total: 14
Semester 2 Course Title Credit Hours
CS 1410 Object-Oriented Programming 3
ENGL 2010 Intermediate Writing Academic Writing and Research 3
MATH 1220 Calculus II 4
PHYS 2210 Physics for Scientists and Engineers I 4
PHYS 2215 Physics for Scientists and Engineers I Lab 1
  Semester total: 15
Semester 3 Course Title Credit Hours
CS 2300 Discrete Mathematical Structures I 3
CS 2420 Introduction to Algorithms and Data Structures 3
MATH 2210 Calculus III 4
GE Choose from American Institutions distribution list 3
GE Choose from Biology Distribution list 3
  Semester total: 16
Semester 4 Course Title Credit Hours
CS 3520 Database Theory 3
MATH 2270 Linear Algebra 3
CS 2700 Causal Inference 3
GE Choose from HLTH 1100 or EXSC 1097 2
GE Third Science Distribution 5
  Semester total: 16
Semester 5 Course Title Credit Hours
CS 3530 Data Management for Data Sciences 3
CS 3270
Python Software Development 3
ECE 3710 Applied Probability and Statistics for Engineers and Scientists 3
COMM 2110 Interpersonal Communication 3
CDS Elective   3
  Semester total: 15
Semester 6 Course Title Credit Hours
CS 3800 Data Science Through Statistical Reasoning 3
CS 3320 Numerical Software Development 3
CS 3820 Visualization Analytics for Data Science 3
GE Choose from Fine Arts Distribution list 3
CDS Elective   3
  Semester total: 15
Semester 7 Course Title Credit Hours
CS 3810 Applied Data Science 3
CS 4700 Machine Learning I 3
CS 3100 Data Privacy and Security 3
PHIL 2050 or PHIL 205G Ethics and Values 3
CDS Elective   3
  Semester total: 15
Semester 8 Course Title Credit Hours
CS 4800 Data Science Capstone 3
CS 4710 Machine Learning II 3
CS 305G Global Social and Ethical Issues in Computing 3
COMM 1020 Public Speaking 3
CDS Elective   3
  Semester total: 15
  Degree total: 121

Department

Computer Science

The Computer Science department is in the   Scott M. Smith College of Engineering. To find the most up-to-date information, including Program Learning Outcomes for degree programs offered by the Computer Science department, visit their website.

Computer Science department