Data Science - BS

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College of Science

Department of Mathematics and Statistics

Department of Computer Science

About This Degree:

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.

For more information about Mathematics, see the website.
Admitted and current students must meet with Linda Skabelund.
Log on to Degree Works to check student-specific program progress.

Minimum University Requirements

Total Credits: 120
Credits of C- or better: 100
Total credits taken through USU: 30
Total major required credits taken at USU: 10
Minimum Grade Point Average (many majors require a higher GPA): 2.0 GPA
Credits of upper-division courses (#3000 or above): 40
Upper-division credits taken at USU: 20
General Education Requirements
University Studies Requirements
Undergraduate Degree Requirements

Admission Requirements For This Program

New freshmen must be admitted to USU in Good Standing.
Transfer students from other institutions or other programs at USU must have a 2.75 GPA.

Major Requirements

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

College of Science Sequence Requirement (6-8 credits)

Students must choose one of the following five sequences:

BIOL 1610 - Biology I 3 credit(s) and
BIOL 1620 - Biology II (BLS) 3 credit(s)
or
CHEM 1210 - Principles of Chemistry I 4 credit(s) and
CHEM 1220 - Principles of Chemistry II (BPS) 4 credit(s)
or
GEO 1110 - Physical Geology (BPS) 3 credit(s) and
GEO 1115 - Physical Geology Laboratory 1 credit(s) and
GEO 2200 - The Earth Through Time 3 credit(s)
or
PHYS 2110 - General Physics - Life Sciences I 4 credit(s) and
PHYS 2120 - General Physics - Life Sciences II (BPS) 4 credit(s)
or
PHYS 2210 - Physics for Scientists and Engineers I (BPS/QI) 4 credit(s) and
PHYS 2220 - Physics for Scientists and Engineers II (BPS/QI) 4 credit(s)

Data Domain (6 credits)

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

BIOL 2060 - Elementary Microbiology 4 credit(s)
BIOL 2220 - General Ecology 3 credit(s)
BIOL 3060 - Principles of Genetics (QI) 3 credit(s)
BIOL 3065 - Genetics Laboratory (CI) 2 credit(s)
BIOL 4230 - Applied Mathematics in Biology (QI) 3 credit(s)
BIOL 4270 - Theoretical Ecology 3 credit(s)
BIOL 4450 - Neurobiology 3 credit(s)
CHEM 2300 - Principles of Organic Chemistry 3 credit(s)
CHEM 2310 - Organic Chemistry I 4 credit(s)
CHEM 2320 - Organic Chemistry II 4 credit(s)
CHEM 3000 - Quantitative Analysis (QI) 3 credit(s)
CHEM 3060 - Physical Chemistry I (QI) 3 credit(s)
CHEM 3070 - Physical Chemistry II (QI) 3 credit(s)
CHEM 3700 - Introductory Biochemistry 3 credit(s)
GEO 2800 - Minerals and Rocks 4 credit(s)
GEO 3100 - Natural Disasters (DSC) 3 credit(s)
GEO 3150 - Energy in the Twenty-first Century (DSC/QI) 3 credit(s) OR
PHYS 3150 - Energy in the Twenty-first Century (DSC/QI) 3 credit(s)
GEO 3300 - Geology of the World’s Oceans (DSC) 3 credit(s)
GEO 3550 - Sedimentation and Stratigraphy 4 credit(s)
GEO 3600 - Geomorphology 4 credit(s)
GEO 3700 - Structural Geology 4 credit(s)
GEO 4500 - Igneous and Metamorphic Petrology 4 credit(s)
GEO 5640 - Introduction to Seismology 3 credit(s)
GEO 5670 - Inverse Theory 3 credit(s)
PHYS 2500 - Introduction to Computer Methods in Physics 2 credit(s)
PHYS 2710 - Introductory Modern Physics 3 credit(s)
PHYS 3010 - Space Exploration from Earth to the Solar System (DSC/QI) 3 credit(s)
PHYS 3030 - The Universe (DSC/QI) 3 credit(s)
PHYS 3040 - Space Weather–Dangers to the High-Tech World (QI) 3 credit(s)
PHYS 3550 - Intermediate Classical Mechanics 3 credit(s)
PHYS 3600 - Electromagnetism I 3 credit(s)
PHYS 3700 - Thermal Physics 3 credit(s)
PHYS 3710 - Intermediate Modern Physics 3 credit(s)
PHYS 4650 - Optics I 3 credit(s)
ECN 2010 - Introduction to Microeconomics (BSS) 3 credit(s)
ECN 3010 - Managerial Economics (DSS) 3 credit(s)
ECN 3170 - Law and Economics 3 credit(s)
ECN 3400 - Introduction to Global Economic Institutions and Business Environment (DSS) 3 credit(s)
ECN 4010 - Intermediate Microeconomics 3 credit(s)
ECN 4020 - Intermediate Macroeconomics 3 credit(s)
ECN 4310 - Mathematical Methods in Economics and Finance I (QI) 3 credit(s)
ECN 4330 - Introduction to Econometrics (QI) 3 credit(s)
ECN 5090 - Machine Learning in Economics and Finance 3 credit(s)
FIN 3200 - Fundamentals of Finance I (QI) 3 credit(s)
FIN 3300 - Fundamentals of Finance II 3 credit(s)
FIN 4200 - Intermediate Corporate Finance 3 credit(s) OR
CS 4460 - Introduction to Cybersecurity 3 credit(s)
PSC 2010 - Soils, Waters, and the Environment (BPS) 3 credit(s)
PSC 3000 - Fundamentals of Soil Science 4 credit(s)
PSC 3600 - An Introduction to Plant Breeding and Heredity 3 credit(s)
PSC 4123 - Climate Data Analysis 3 credit(s)
PSC 4150 - Bioinformatics and Big Data Mining 3 credit(s)
PSC 4810 - Climate and Climate Change (DSC/QI) 3 credit(s)
PSC 6125 - Climate Modeling and Simulation 3 credit(s)
NDFS 2040 - Fundamentals of Food Processing 3 credit(s)
NDFS 3110 - Food, Technology, and Health (DSC) 3 credit(s)
APEC 2500 - Commodity Futures and Options Trading and Analysis 3 credit(s)
APEC 3010 - Agricultural Economics (DSS) 3 credit(s)
APEC 3012 - Introduction to Natural Resource Economics (DSS) 3 credit(s)
WILD 2800 - Introduction to Geographic Information Sciences 4 credit(s) OR
GEOG 2800 - Introduction to Geographic Information Sciences 4 credit(s)
WILD 3810 - Wildlife Population Ecology 3 credit(s)
WILD 4600 - Conservation Biology 3 credit(s)
WILD 5750 - Applied Remote Sensing 3 credit(s)
GEOG 3100 - Human-Environment Geography (CI) 3 credit(s)
GEOG 3800 - Geospatial Data Visualization 3 credit(s)
ENVS 3300 - Fundamentals of Natural Resource Recreation Management 3 credit(s)
ENVS 4000 - Human Dimensions of Natural Resource Management (DSS) 3 credit(s)
ENVS 4100 - Introduction to Modeling Human-Environment Systems 3 credit(s)
ENVS 5550 - Sustainability: Concepts and Measurement 3 credit(s)
POLS 3000 - Introduction to Political Research (QI) 3 credit(s)
POLS 3110 - Parties and Elections (DSS) 3 credit(s)
POLS 4220 - Ethnic Conflict and Cooperation (CI/DSS) 3 credit(s)
POLS 5000 - Political Analysis (QI) 3 credit(s)
ANTH 4170 - Ethnographic Methods in Anthropology 3 credit(s)
SOC 3120 - Social Statistics I (QI) 3 credit(s)
SOC 4230 - Techniques of Demographic Analysis 3 credit(s)
PSY 3400 - Analysis of Behavior: Advanced (DSS) 4 credit(s)
PSY 3500 - Research Methods in Psychology (CI/DSS) 3 credit(s)
COMD 2600 - Introduction to Communication Disorders 3 credit(s)
COMD 3100 - Speech Science 3 credit(s)
COMD 3200 - Child Language Development 3 credit(s)
COMD 3500 - Phonetics and Phonological Development 3 credit(s)
COMD 3800 - Anatomy and Physiology of Speech and Hearing 3 credit(s)
COMD 4450 - Developmental Communication Disorders 3 credit(s)
COMD 4700 - Basic Audiology 3 credit(s)
COMD 5240 - Neural Bases of Cognition and Communication 3 credit(s)
COMD 5330 - Aural Rehabilitation 3 credit(s)
KIN 4400 - Measurement and Evaluation in Kinesiology (QI) 3 credit(s)

Data Science Electives (12 credits)

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.

STAT 5080 - Data Technologies 2 credit(s)
STAT 5120 - Statistical Methods for Rates and Proportions 2 credit(s)
STAT 5170 - Time Series and Forecasting 2 credit(s)
STAT 5200 - Analysis of Designed Experiments 3 credit(s)
STAT 5410 - Applied Spatial Statistics 2 credit(s)
STAT 5500 - Biostatistics Methods 3 credit(s)
STAT 5555 - Advanced R Programming for Data Science 3 credit(s)
STAT 5560 - Statistical Visualization II 2 credit(s)
STAT 5570 - Statistical Bioinformatics 2 credit(s)
STAT 6655 - Machine Learning 3 credit(s)
MAE 5370 - Optimization for Engineers 3 credit(s)
DATA 4330 - Advanced Database and Database Analytics 3 credit(s)
CS 3430 - Scientific Computing (DSC/QI) 3 credit(s) OR
MATH 4610 - Fundamentals of Numerical Analysis 3 credit(s)
CS 4320 - Applied Machine Learning 3 credit(s)
CS 5000 - Theory of Computability 3 credit(s)
CS 5030 - High Performance Computing 4 credit(s)
CS 5050 - Advanced Algorithms 3 credit(s)
CS 5060 - Decision Making: Algorithms Under Uncertainty 3 credit(s)
CS 5080 - Data Mining 3 credit(s)
CS 5110 - MultiAgent Systems 4 credit(s)
CS 5250 - Introduction to Cloud Development 3 credit(s)
CS 5260 - Developing Distributed Software Applications Using Cloud Services (DELETED 2/16/2024) 2 credit(s)
CS 5510 - Robot Intelligence 4 credit(s)
CS 5600 - Intelligent Systems 4 credit(s)
CS 5620 - AI Applications In Education 3 credit(s)
CS 5640 - Artificial Neural Networks 3 credit(s)
CS 5665 - Machine Learning for Data Science 3 credit(s)
CS 5680 - Computer Vision: Foundations and Applications 3 credit(s)
CS 5800 - Introduction to Database Systems 3 credit(s)
CS 5830 - Data Science in Practice 3 credit(s)
CS 5840 - Graph Mining 3 credit(s)
CS 5850 - Introduction to Data Analysis 3 credit(s)
CS 5890 - Topics in Computer Science 1-4 credit(s)
CS 6665 - Data Mining 3 credit(s)
MATH 2280 - Ordinary Differential Equations (QI) 3 credit(s)
MATH 4310 - Introduction to Algebraic Structures (CI) 3 credit(s)
MATH 4410 - Discrete Math 2 4 credit(s)
MATH 5210 - Introduction to Analysis I 3 credit(s)
MATH 5220 - Introduction to Analysis II 3 credit(s)
MATH 5270 - Complex Variables 3 credit(s)
MATH 5310 - Introduction to Modern Algebra 3 credit(s)
MATH 5340 - Theory of Linear Algebra 3 credit(s)
MATH 5410 - Methods of Applied Mathematics 3 credit(s)
MATH 5420 - Partial Differential Equations 3 credit(s)
MATH 5510 - Introduction to Topology 3 credit(s)
MATH 5610 - Computational Linear Algebra 2 credit(s)
MATH 5760 - Applied Stochastic Processes 2 credit(s)

Open Electives

Total elective credit is determined by General Education courses taken, degree type selected, additional credits earned, and any additional math or other prerequisite courses needed. Please consult your Academic Advisor for details.

Total Credits: 120

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