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Introduction to R Programming (2 Day Class)

Class Code

ITS-2517

Class Description

Effective immediately in response to COVID-19, all Technology Training classes will be delivered online until further notice.

In advance of each session, Tech Training will provide you with a Zoom link to your class, along with any required class materials.
 



This two-day training course will help you to learn the practical aspects of the R programming language. Hands-on labs will allow attendees to immediately apply their theoretical knowledge in practice. R has various packages covering a wide range of topics such as econometrics, finance, and time series. R has best-in-class tools for visualization, reporting, and interactivity, which are as important to business as they are to science. R is well-suited for scientists, engineers, and business professionals.

Prerequisite: Basic understanding of programming, data structures, and functions.

Course Topics Include:

  • What is R?
  • Introduction to Functional Programming with R
  • Managing Your Environment
  • R-Type System & Structures
  • Extending R
  • Read-Write & Import-Export Operations in R
  • Statistical Computing Features in R
  • Data Manipulation & Transformation in R
  • Data Visualization in R
  • Using R Efficiently
  • Lab Exercises

 

During and at the end of each session, hands-on exercises will be practiced to: 

  1. Building data frames, selecting specific rows and columns, adding columns, and applying functions on columns that contain date values
  2. Downloading public data into R, applying manipulation functions on data records, and summarizing insights from data
  3. Merging datasets by foreign keys, reshaping datasets, selecting random samples from data-frames, and aggregating columns by other columns.
  4. Creating different data visualizations and saving them in different formats.
     


About the Instructor: Arafat Mokhtar

Arafat Mokhtar is a Business Intel Engineer at Stanford School of Medicine, who supports the Human Resources Group with data collections, validation, cleansing, and analytics to provide actionable data insights used by leadership management to make data-driven decisions on the organization workforce. He develops code to automate data analytics processes, proposes data solutions, and develops measurable business metrics.

 

Arafat holds a Ph.D. in Particle Physics and spent several years as a postdoctoral fellow at SLAC National Accelerator Laboratory. He has 10+ years of teaching experience and conducted a number of Python and R training sessions for Stanford Technology Training Programs.

 


University IT Technology Training classes are only available to Stanford University staff, faculty, or students. A valid SUNet ID is needed in order to enroll in a class.