CS533 F18 Info

Though the course has been taught before, this is my first time teaching it and I don't quite have the details worked out, so the information below is subject to change. 

(Undergraduates: if you want to take this course, please contact me.)

Course Goals and Learning Outcomes

  • 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.

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

  • Explore a data set to determine whether and how it might illuminate questions of interest.
  • Define and operationalize a research question such that a data analysis could produce meaningful knowledge.
  • Use best practices to carry out analyses in a documented, reproducible, and efficient fashion.
  • Present the results of a data analysis with appropriate visuals and written argument.
  • Identify weaknesses in a data analysis and assess their impact on the correctness and utility of the results.
  • Assess ethical implications of an analysis in terms of both classical human subject research ethics and contemporary concerns such as fairness and bias.
  • Understand the space of data science techniques and applications, and relate future learning to this framework.

Service Learning This class provides a service-learning opportunity as a semester-long project which gives students hands-on experience applying what they learn in the classroom to a need in the community. The outcomes of service learning are:

  • Experience a real-world project with a client partner and apply important steps in the Data Science process, including:
    • gather requirements and data from the client
    • perform preliminary cleaning and analysis on that data,
    • determine what the data can afford the client,
    • use the data to make inferences or decisions that help the client,
    • explain policies, ethics, etc. related to the project
    • reflect on differences and similarities between how clients think about using data to solve problems, and how data scientists think about using data
    • take into account how data science can promote the common good and tackle issues of public concern

This semester-long service learning project will be evaluated through classroom discussion, peer evaluations, and instructor evaluations.


Quizzes/In-class activities 10%
Assignments 50%
Midterm 20%
Final 20%

We are still considering which book to adopt. If you want to get started with Python and Data Science, I can recommend the online Foundations of Data Science Textbook by By Ani Adhikari and John DeNero.

The assignments (which are more like small-scale projects) require quite a bit of python programming. We'll spend a few lectures in the first part of the semester introducing Python. If a seminar comes up during the semester which seems relevant, I will assign it, but I can't tell that at the moment. 

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