Course Descriptions

CS/DS 125 Introduction to Computer and Data Sciences

Computer science, broadly, studies how to solve problems using computers.  Data science is a related field that focuses on acquiring, cleaning, and exploring data, via visualization and statistical analysis, to aid decision making. This course introduces the fundamental skill of computer science, programming, using data science examples and applications. Offered most semesters. No prerequisites.  

DS 225 Data Analytics with Visualization

An examination of advanced concepts and tools relevant to data cleaning, organization, and transformation. Development of skills and knowledge relevant to identifying and applying statistical tools to answer data-driven questions. Examination of ethical issues in analysis. Introduction to databases and creation of static and interactive reports. Offered every other year.

Prerequisites: 

  • CS/DS 125
  • BIOL 323, ECON 227, MATH 141, MATH 325, or PSYC 227  

CS/DS 377 Applied Data Analysis

This course further develops the programming, mathematical, and statistical skills required for the application of data science tools to data analysis, data visualization, and decision making. This course includes a methodology/writing component in which students develop a draft research proposal for a capstone project. Offered every other year.

Prerequisites:

  • CS/DS 125, CS 126, or CS 127
  • CS/MATH 136
  • BIOL 209, ECON 227, MATH 141, MATH 325, or PSYC 227

DS 395 Directed Study, Data Science Capstone

Individual directed study to complete a capstone project.  Requires an approved proposal for a substantial project that applies data science techniques to gather, clean, analyze, visualize, and make inferences with data.  Project culminates in written and oral reports. Offered as needed.

Prerequisites:

  • CS/DS 377
  • Approval of the program director.