Nov 29, 2024  
2023-2024 General Catalog 
    
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Data Science – BS


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College of Science

Department of Mathematics and Statistics

Department of Computer Science

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  • For more information about Mathematics, see the website.
  • Following is a sample four-year plan. Please note that student-specific plans may differ.
  • Admitted students must meet with Linda Skabelund. Current students should also meet with Linda Skabelund and log on to Degree Works  to check student-specific program progress.

Minimum University Requirements

Total Credits 120

 

Grade Point Average (most majors require higher GPA)

2.00 GPA
Credits of C- or better 100 Credits of upper-division courses (#3000 or above) 40
Total USU Credits 30 Upper-division USU Credits 20
USU Credits within the Major 10 Credits in Minor (if required) 12
Credits in Major see below Credits in American Institutions 3
General Education Requirements   see link University Studies Depth Requirements   see link
 

Admissions Requirements for this Program

New freshmen Admitted to USU in Good Standing

 

Transfer students from other institutions or other programs at USU 2.75 GPA

 

First Year

 Fall Semester

Credits

General Education Info and Notes:

 

Spring Semester

Credits

General Education Info and Notes:

CS 1400 - Introduction to Computer Science–CS 1   4     CS 1410 - Introduction to Computer Science–CS 2 (QI)   3    
ENGL 1010 - Introduction to Writing: Academic Prose (CL1)   3     MATH 1220 - Calculus II (QL)   4    
MATH 1210 - Calculus I (QL)   4     Breadth Creative Arts (BCA)   3  
College of Science Course 4   CS 1440 - Methods in Computer Science   3    
      College of Science Course (BLS or BPS) 3  
Total 15   Total 16  
Comments

 

Comments

Second Year

 Fall Semester

Credits

General Education Info and Notes:

 

Spring Semester

Credits

General Education Info and Notes:

MATH 2210 - Multivariable Calculus (QI)   3     Breadth Humanities (BHU)   3  
MATH 2270 - Linear Algebra (QI)   3     Data Domain Course 3  
ENGL 2010 - Intermediate Writing: Research Writing in a Persuasive Mode (CL2)   3     STAT 3000 - Statistics for Scientists (QI)   3    
Data Domain Course 3   CS 2420 - Algorithms and Data Structures–CS 3 (QI)   3    
Breadth Social Sciences (BSS)   3   Breadth American Institutions (BAI)   3  
Total 15   Total 15  
Comments

 

Comments

Third Year

 Fall Semester

Credits

General Education Info and Notes:

 

Spring Semester

Credits

General Education Info and Notes:

MATH 3310 - Discrete Mathematics   3     MATH 5720 - Introduction to Mathematical Statistics   3    
MATH 5710 - Introduction to Probability   3     MATH 4200 - Foundations of Analysis (CI)   3    
STAT 5645 - Mathematical Methods for Data Science  or  MATH 5645 - Mathematical Methods for Data Science   3  or 3     STAT 5650 - Statistical Learning and Data Mining I   2    
STAT 5100 - Modern Regression Methods (CI/QI)   3     CS elective 3  
DATA 3330 - Database Management   3     Breadth Life Sciences (BLS)  or Breadth Physical Sciences (BPS)   3  
STAT 5050 - Introduction to R   1     Electives 1-2  
Total 16   Total 15-16  
Comments

 

Comments

Fourth Year

 Fall Semester

Credits

General Education Info and Notes:

 

Spring Semester

Credits

General Education Info and Notes:

STAT 5685 - Deep Learning Theory and Applications   3     STAT elective 2  
STAT elective 2   Data Science elective  
Data Science elective 3   Depth Social Sciences (DSS)   2 or 3  
STAT 5550 - Statistical Visualization I  or  CS 5820 - Data Science - Data Visualization   2  or 3     Electives 6  
PHIL 3520 - Business Ethics (DHA)  or  PHIL 3530 - Environmental Ethics (DHA)   3  or 3          
Electives 1        
Total 14 or 15   Total 13 or 14  
Comments

 

Comments

 


Data Science is an interdisciplinary field that includes the management, analysis, and visualization of data to make the best possible evidence-based decisions, and draws primarily from the fields of Statistics and Computer Science. This data science degree prepares students for doing science in an era of big data. The program includes a core set of classes from mathematics, statistics, and computer science in addition to core and elective courses in data science. A rigorous foundation in these areas will prepare students to: 1) use modern database tools, programming languages, and algorithms to build, clean, manage, process, and analyze large datasets; 2) accurately interpret and analyze data to facilitate forecasting, prediction, and decision making; and 3) understand the underlying mechanics, assumptions, strengths, and weaknesses of conventional and modern data science methods so that students can apply the methods appropriately and develop new data science methods when needed.

All grades for MATH, STAT, and CS courses applied toward the Data Science major must be C- or better.

Data Domain


Students will take at least 6 credits from the following list:

Data Science Electives


Students will take 12 credits from the following list. At least 3 credits must be in STAT and at least 3 credits must be in CS. Courses in data science at the 6000-level are also allowed as approved.

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