Data Science BS General (67-68 credits)

The Data Science BS provides students fundamental training for the field of Data Science while allowing students the flexibility to explore data science applications in many areas of study. If you have questions about the degree program or need advising, please email data.science.advising@ucdenver.edu with your inquiry.

 

The course requirements below summarize the data science-related course requirements but do not describe broader university or college degree requirements. Additional program requirements related to GPA, minimum grades, credit hours, restrictions, etc. are provided in the university catalog description of the Data Science BS.

 

Course Requirements

 

Required courses

 

MATH 1401: Calculus I

MATH 2411: Calculus II

MATH 2421: Calculus III

MATH 3376: Data Wrangling & Visualization

MATH 3382: Statistical Theory

MATH 3810: Introduction to Probability

MATH 4387: Applied Regression Analysis

MATH 4388: Machine Learning Methods

CSCI 1410: Fundamentals of Computing and CSCI 1411: Fundamentals of Computing Laboratory

BMIN 1000: Introduction to Business

ISMG 2050: Business Problem Solving Tools

ISMG 3500: Business Data and Database Management

ISMG 3110: Data Governance and Ethics

 

Choose one:

  • CSCI 2980: Foundations of Data Science
  • MATH 2830: Introductory Statistics

 

Choose one:

  • MATH 3191: Applied Linear Algebra
  • MATH 3195: Linear Algebra and Differential Equations

 

Choose one path:

  • UNIV 1110: College Success and BUSN 2110: Cultivating Emotional Intelligence and BUSN 3110: Career and Professional Development
    or
  • BMIN 2200: Career and Professional Development

 

Choose one:

  • BANA 4110: Business Analytics Processes
  • BANA 4120: Forecasting Techniques
  • BANA 6610: Statistics for Business Analytics
  • BANA 6620: Computing for Business Analytics
  • BANA 6670: Prescriptive Analytics with Optimization
  • BANA 6710: Causal Analysis
  • BANA 6770: Evaluative Analytics

 

Choose one:

  • MATH 4779: Math Clinic
  • MATH 3939: Internship*
  • MATH 4840: Independent Study*
  • ISMG 3939: Internship*
  • ISMG 4840: Independent Study*
  • CSCI 4840: Independent Study*
  • CSCI 4939: Internship*

*Requires the approval of the Director of Data Science and an advisor for the course. CSCI 4840 or 4939 will only be approved for the Computer Science option. Must be taken for 3 credit hours.

 

Electives

 

Choose nine additional elective credits not previously taken from any of the courses listed below.

 

  • BANA 4110: Business Analytics Processes 
  • BANA 4120: Forecasting Techniques
  • BANA 6600: Transformative Technologies Impacting Globalization
  • BANA 6610: Statistics for Business Analytics
  • BANA 6620: Computing for Business Analytics
  • BANA 6630: Time-Series Forecasting
  • BANA 6640: Decision Analysis
  • BANA 6650: Project Management
  • BANA 6660: Predictive Analytics
  • BANA 6670: Prescriptive Analytics with Optimization
  • BANA 6710: Causal Analysis
  • BANA 6730: Supply Chain Analytics
  • BANA 6760: Data Visualization
  • BANA 6770: Evaluative Analytics
  • BANA 6780: AI for Business​
  • BANA 6800: Special Topics
  • CHEM 4521: Physical Chemistry: Quantum and Spectroscopy​
  • CHEM 4580: Molecular Informatics​
  • CHEM 4640: Artificial Intelligence in Chemistry and Biochemistry​
  • CHEM 4845: Molecular Modeling and Drug Design
  • CMDT 4782: Commodity Data Analysis
  • CSCI 4455: Data Mining
  • CSCI 4702: Big Data Mining
  • CSCI 4788: Bioinformatics
  • CSCI 4800: Special Topics* (must be relevant to Data Science)
  • CSCI 4930: Machine Learning
  • CSCI 4931: Deep Learning
  • CSCI 4951: Big Data Systems
  • ECON 4030: Data Analysis with SAS​
  • ECON 4811: Introduction to Econometrics
  • ECON 4812: Advanced Econometric Methods
  • GEOG 4060: Remote Sensing I: Introduction to Environmental Remote Sensing
  • GEOG/GEOL 4070: Remote Sensing II: Advanced Remote Sensing
  • GEOG 4080: Geographic Information Systems
  • GEOG 4081: Introduction to Cartography and Computer Mapping
  • GEOG 4085: GIS Applications for the Urban Environment
  • GEOG 4090: Environmental Modeling with GIS
  • GEOG 4091: Open Source Software for Geospatial Applications
  • GEOG 4092: GIS Programming and Automation
  • GEOG 4095: Deploying GIS Functionality on the Web
  • GEOG 4235: GIS Applications in the Health Sciences
  • ISMG 3000: Technology in Business
  • ISMG 3600: System Strategy, Architecture and Design
  • ISMG 4300: Information Systems Security and Privacy
  • ISMG 4750: Business Intelligence in Finance
  • ISMG 4900: Project Management and Practice
  • ISMG 6080: Database Management Systems
  • ISMG 6470: Text Data Analytics
  • MATH 3200: Elementary Differential Equations
  • MATH 3301: Introduction to Optimization
  • MATH 4390: Game Theory
  • MATH 4408: Applied Graph Theory
  • MATH 4650: Numerical Analysis I
  • MATH 4660: Numerical Analysis II
  • MATH 4733: Partial Differential Equations
  • MATH 4792: Probabilistic Modeling
  • MKTG 3100: Marketing Research
* Subject to pre-requisite requirements as well as approval of the Director of Data Science and course instructor.

 

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