Course Directors: Dr. Ramesh Yapalparvi
- Course description: This course introduces techniques which enables students to pull data from various sources and to work with different forms of data. This course will cover the basics of importing tabular and spreadsheet data, scraping data stored online, and exporting data for sharing purposes. Writing a simple, replicable, and readable code is important to becoming an effective and efficient data scientist. Throughout this course, you will be introduced to the art of writing functions and using loop control statements to reduce redundancy in code. You will also learn how to simplify your code using various operators to make your code more readable. Data wrangling is all about getting your data into the right form in order to feed it into the visualization and modeling stages. This typically requires a large amount of reshaping and transforming of your data. Throughout this course, you will learn the fundamental functions for “tidying” your data and for manipulating, sorting, summarizing, and joining your data. These tasks will help to significantly reduce the time you spend on the data wrangling process. Lastly, data visualization is a key component that all data scientist needs to be fluent in. Students will become competent users of Tableau. A course of data visualization will help students spend plenty of time learning to properly visualize your data.
- Coursework: Calculus and Algebra.
- Programming: Intermediate programming experience in R.