Course code:

ES1064

Level:

I - Introductory

Class size limit:

15

Meets the following requirements:

  • QR - Quantitative Reasoning
  • ES - Environmental Science

Typically offered:

Yearly

Data Science is an interdisciplinary field that encompasses data exploration, statistical modeling, and visualization. Data Science has broad applicability to the natural and social sciences and can be used to guide health and policy decisions. Students interested in analyzing data from the natural or social sciences should take this course. Students who complete this course will be able to: 1. organize data to be correctly read by computer software; 2. subset, transform and summarize data to understand its structure; 3. explore relationships in data through creative visualization; 4. ask questions of the data by fitting the appropriate statistical models; and 5. produce clear and convincing visualizations that support major conclusions from the data.

Most classes will be taught through live coding exercises in which students will write code simultaneously with the instructor. The course will emphasize rigorous practices that lead to reproducible research by scripting analyses and versioning of data and results. Students will be encouraged to bring data from their own interests to the class. Students who do not have data will be able to select from several data sets from the social and physical sciences. Examples of data sets might be: temperature change over time, animal population data, election results or wage and income data. No prior programming experience is required. Students will need to use either their personal laptop or a COA loaner laptop for class and programming exercises. Evaluation will be through class participation, quizzes, homework and a final project.

Always visit the Registrar's Office for the official course catalog and schedules.