The purpose of this course is for students to learn how to engage in the scientific process using data-centric concepts and methods and to think like a data scientist by critically analyzing their own work and the work of others.

Learning Outcomes#

It is my goal that after completing this course successfully, you will be able to:

  1. Explore a data set to determine whether and how it might illuminate questions of interest.

  2. Define and operationalize a research question such that a data analysis could produce meaningful knowledge.

  3. Use best practices to carry out analyses in a documented, reproducible, and efficient fashion.

  4. Present the results of a data analysis with appropriate visuals and written argument.

  5. Identify weaknesses in a data analysis and assess their impact on the correctness and utility of the results.

  6. Assess ethical implications of an analysis in terms of both classical human subject research ethics and contemporary concerns such as fairness and bias.

  7. Understand the space of data science techniques and applications, and relate future learning to this framework.


The following sections of the syllabus provide detailed information on course structure and policies: