Course Overview

This course will cover the fundamental and practical concepts in programming, statistical computing, data wrangling, and visualization using R. R is a highly versatile software that can be very useful for health data analytics. By the end of the course, students are expected to have a solid understanding of R's functionality for data manipulation, visualization, and statistical computing. We will not be spending a lot of time on the preliminaries (formulas, algorithms) to use that time to prepare you for the exciting part of statistics––being able to process and investigate your data for a problem that matters to you.

Type Lecture


Perman Gochyyev, PhD


3 undergraduate


Online Asynchronous




$1,575.00 (Fees included)

What to Expect in this Course

This course is fully asynchronous – there are no required meeting times.

Course activities are organized into modules that are usually 1 week in length. 

Our format allows flexibility so you can fit the learning activities into your own schedule. 

While instructors make regular course updates to enhance your experience as a learner, the table below provides a general idea of what you can expect from a typical week.

Course Activity Hours Per Week

Self Directed Learning

  • Reading textbooks, articles
  • Watching mini-lectures, videos
  • Listening to podcasts


  • Mini quizzes
  • Practice problems
  • Weekly modules

Other Assignments

  • Written papers
  • Case studies
  • Practical assignments

Discussion Boards

  • Initial posting
  • Reading posts
  • Responding to peer posts
Total Time 10-15
  • How to read data
  • How to manage different types of variables and missing values
  • How to work with data frames
  • How to create functions
  • How to generate data summaries
  • Strategies for visualization
  • How to process text data and use regular expressions
  • How to model continuous outcomes using linear regression model
  • How to model categorical outcomes using logistic regression model

Course Materials

D2L Required
Textbook Not needed
Lab Kit / Supplies Not needed
Web-Based Learning Application Required
Standard word/ data processing capabilities Required
Ability to Video conference Recommended
Ability to upload images/videos Not needed

D2L: All of our online prerequisite courses use the learning platform software called Desire2Learn (D2L). D2L integrates text, video, and audio. You can check your system compatibility by reviewing the D2L system recommendations.

Textbook: If a textbook is required, every effort is made to choose high-quality, low-cost materials that students can buy and sell, rent and return, or buy and use again in future courses.

Lab Kit / Supplies: Lab kits/supplies allow students to conduct hands-on experiments at home. Information about ordering lab kits and/or supplies will be provided to registered students approximately 6 weeks before the start of the semester.

Web-Based Learning Application: Web-based applications often serve as an alternative to a traditional textbook or lab kit. Most require students to register for a separate application that will integrate seamlessly with the D2L platform.

Standard word and data processing: Technology that allows the student to create, edit, and save documents and files.

Ability to videoconference: Technology that allows live, visual connection between individuals who are in different locations.

Ability to upload photos/videos: Technological capabilities through which a student could record a short video or still image and upload it to an online learning system.

Course Faculty

Perman Gochyyev, PhD

Assistant Professor Healthcare Data Analytics

Assistant Professor Healthcare Data Analytics

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