DAT204x: Introduction to R for Data Science

Course Prerequisites None, but previous experience in basic mathematics is helpful.

Course Schedule

This course is available in self paced format. Deadlines associated with the graded quizzes and labs are set to the end date of the course, which is displayed on the course Homepage. You can listen to the lecture, attempt the quizzes, and work on the labs exercises at any time prior to the deadline. Yo u should complete the quizzes/labs on your own to fully learn the material before you start the next module.

Course Topics

Module 1: Introduction to Basics

Take your first steps with R. Discover the basic data types in R and assign your first variabl e.

Module 2: Vectors

Analyze gambling behavior using vectors. Create, name and select elements from vectors.

Module 3: Matrices

Learn how to work with matrices in R. Do basic computations with them and demonstrate your knowledge by analyzing the Star Wars box office figures.

Module 4: Factors

R stores categorical data in factors. Learn how to create, subset and compare categorical data.

Module 5: Lists

Lists allow you to store components of different types. Learn how to work with lists.

Module 6: Data Frames

When working R, you’ll probably deal with Data Frames all the time. Therefore, you need to know how to create one, select the most interesting parts of it, and order them.

Module 7: Basic Graphics

Discover R’s packages to do graphics and create your own data visualizations

Expected Effort

Each module, you should expect to spend 1-2 hours on the course, including:

  • Viewing the lecture videos and demonstrations

  • Completing the quizzes

  • Completing the lab exercises

  • Further reading

Coursework and Grading

This course includes coursework, some of which is graded. Each module in the course includes lecture videos, graded short quizzes, and graded lab exercises. The quizzes account for 30% of the total grade, the lab exercises accounts for 65% of the total grade, and the mandatory survey accounts for the remaining 5%. You must achieve an overall score of 70% to pass the course. For the quizzes/labs questions, you have between one to four maximum attempts at each question, depending on the type of the question.