Meeting Time: TR 9-10:45am
Dr. Ladd’s Student Drop-In Hours: T 11am-12pm & W 1-3pm in TECH 201
or email for appointment, email@example.com
From social media to the James Webb telescope, from Shakespeare’s plays to the U.S. Census, data is being collected all around us, all the time. How can we make sense of these near-constant streams of information?
This course will attempt to answer this question by introducing the concepts and practices involved in data analysis: data collection and preparation, exploratory analysis, and prediction and classification. Using the programming language Python and other industry-standard tools, we will practice ways of working with data from simple summary statistics to advanced machine learning models. At each step of the way, we’ll discuss how to approach data analysis critically and ethically. And we’ll explore data sets from a wide range of fields and disciplines, including sociology, ecology, business, film, and history.
At the end of this course, you should be able to:
- Understand and implement the data analysis process, from data collection to communicating results.
- Use exploratory data analysis to quickly understand a complex dataset.
- Apply modeling techniques to make predictions.
- Evaluate the effectiveness of different modeling techniques.
- Think and act ethically at all steps of the data analysis process.