Course Syllabus

Welcome to PRDV420: Introduction to R Programming

Specific information about this course and its requirements can be found below. For more general information about taking Saylor Academy courses, including information about Community and Academic Codes of Conduct, please read the Student Handbook.


Course Description

Learn the basics of data manipulation and visualization in R – the world’s most popular language for statistical computing – even if you do not have prior programming experience.


Course Introduction

Data analysis is essential for discovering trends and correlations and making informed decisions. The R programming language and software environment offer a free and ever-growing data analysis and visualization resource collection. Nowadays, R is used in governmental organizations, academia, and industry (that is, everywhere) for everything from sales forecasting and evaluating the impact of a marketing campaign to studying new health treatments.

The course provides hands-on experience for learning R language basics and engages students in programming in this open-source language for statistical computing. This course is for all new R users and does not require prior programming experience. You will learn the foundations -- how to install R and load data into it -- and continue with data manipulation, visualization, and implementation of standard statistical functions. By the end of the course, you will be able to find relevant R resources (packages), read R code, and write your code to visualize and analyze your data.

This course includes the following units:

  • Unit 1: Introduction to R and RStudio
  • Unit 2: Basic Object Types and Operations in R
  • Unit 3: Data Import and Export
  • Unit 4: Data Visualization
  • Unit 5: Common Statistical Functions


Course Learning Outcomes

Upon successful completion of this course, you will be able to:

  • install and update R, R packages, and the RStudio interface on your computer;
  • operate with common types of R objects;
  • import and export data for analysis;
  • visualize data using R; and
  • work with common statistical functions.

Throughout this course, you will also see learning outcomes in each unit. You can use those learning outcomes to help organize your studies and gauge your progress.


Course Materials

The primary learning materials for this course are readings, lectures, and videos.

All course materials are free to access and can be found in each unit of the course. Pay close attention to the notes that accompany these course materials, as they will tell you what to focus on in each resource, and will help you to understand how the learning materials fit into the course as a whole. You can also see a list of all the learning materials in this course by clicking on Resources in the navigation bar.


Evaluation and Minimum Passing Score

Only the final exam is considered when awarding you a grade for this course. In order to pass this course, you will need to earn a 70% or higher on the final exam. Your score on the exam will be calculated as soon as you complete it. If you do not pass the exam on your first try, you may take it again as many times as you want, with a 7-day waiting period between each attempt. Once you have successfully passed the final exam you will be awarded a free Course Completion Certificate.

There are also end-of-unit assessments in this course. These are designed to help you study, and do not factor into your final course grade. You can take these as many times as you want to, until you understand the concepts and material covered. You can see all of these assessments by clicking on Quizzes in the course's navigation bar.


Tips for Success

PRDV420: Introduction to R Programming is a self-paced course, which means that you can decide when you will start and when you will complete the course. There is no instructor or set schedule to follow. We estimate that the "average" student will take 13 hours to complete this course. We recommend that you work through the course at a pace that is comfortable for you and allows you to make regular progress. It's a good idea to also schedule your study time in advance and try as best as you can to stick to that schedule.

Learning new material can be challenging, so we've compiled a few study strategies to help you succeed:

  • Take notes on the various terms, practices, and theories that you come across. This can help you put each concept into context, and will create a refresher that you can use as you study later on.
  • As you work through the materials, take some time to test yourself on what you remember and how well you understand the concepts. Reflecting on what you've learned is important for your long-term memory, and will make you more likely to retain information over time.


Technical Requirements

This course is delivered entirely online. You will be required to have access to a computer or web-capable mobile device and have consistent access to the internet to either view or download the necessary course resources and to attempt any auto-graded course assessments and the final exam.

  • To access the full course including assessments and the final exam, you will need to be logged into your Saylor Academy account and enrolled in the course. If you do not already have an account, you may create one for free here. Although you can access some of the course without logging in to your account, you should log in to maximize your course experience. For example, you cannot take assessments or track your progress unless you are logged in.

For additional guidance, check out Saylor Academy's FAQ.



This course is entirely free to enroll in and to access. Everything linked in the course, including textbooks, videos, webpages, and activities, are all available for no charge. This course also contains a free final exam and course completion certificate.

Last modified: Tuesday, January 17, 2023, 4:26 PM