6 The DataCamp Courses

Students in my discussion sections will be introduced to R programming through interactive programming exercises and short lectures hosted on a website about Data Science education called DataCamp. These exercises and lectures are divided into several different topics and constitute different short courses on the DataCamp website.

Normally, access to most DataCamp courses requires a paid subscription. However, DataCamp gives free temporary licenses to students who are taking DataCamp courses as part of a class like ours through their education initiative. These courses are graded material in our class.

6.0.1 Basic programming

The following courses must be completed during winter break and prior to the start of the semester. I recommend starting them right away for a couple of reasons. First, this will give you time to think deeply about how to apply what you learn in the lectures to each task, which will help you perform better. Second, taking your time will also help the concepts sink in, which will help you later when you’re reading the tutorials that have been written for this course and you’re trying to complete your lab work. Finally, each course will probably take you a few hours to complete. If you wait until the last minute, you won’t have enough time to get them all done before the deadline.

  1. Introduction to R
  2. Introduction to Tidyverse
  3. Intermediate R
  4. Data Visualization with ggplot2 (Part 1)
  5. Data Visualization with ggplot2 (Part 2)
  6. Introduction to Writing Functions in R

6.0.2 Extra practice

The following courses will be assigned as extra homework. Keep an eye out for announcements. This list may also be updated to add more courses.

  1. Foundations of Probability in R
  2. Probability Puzzles in R
  3. Exploratory Data Analysis
  4. Exploratory Data Analysis in R: Case Study