Introduction to R for Data Science [Workshop]

Submitted Apr 15, 2019

R programming is one of the most popular programming languages used in Data Science. Known for its simplicity and easy to take off working environment, R has been the language of choice of many non-programmers and its Rich ecosystem enables it to perform variety of Data Science related tasks. The objective of this workshop is to help you get started with R for you to move forward with your Data Science journey. As we are moving into the world of language-agnostic developers, Even if you know a language already, knowing another extra programming language like R would add an extra feather to your cap.


Workshop Outline

  1. Introduction to R & RStudio

  2. RStudio Overview

  3. Basics of R Programming

  4. Data wrangling and Visualization using Tidyverse

  5. Documentation and Reporting using R Markdown

  6. Sample R Projects

    Duration of the workshop:: 3 Hours (Basics R) + ~2 Hours (R for Data analysis)
    Background knowledge required to participate in the workshop:: This material is designed for even Non-programmers (Statisticians and Economists) to start with R.
    What concepts/technologies should participants be familiar with in order to attend the workshop.: A little bit of some programming language idea would help.
    Target audience: who should attend the workshop?: A SAS/Data Scientist wanting to learn R to couple with their existing Tech stack.
    Who should NOT attend this workshop.: Anyone who has read an R book or even some bit of R book wouldn’t need to attend, as it might seem very reduntant.
    Why attend this workshop? What will participants learn from attending this workshop? How will they benefit?: Data science Tech stack is vast and huge with individual advantages. Having a langauge like R in your toolkit would be really valuable. For example: R has rich set of Bayesian tools and DSLs of R are quite extensive/customizable/useful. Participants will learn to start with R thus setting up the base layer for further development like NLP with R / Automated Dashboarding/Reporting using R.
    Detailed workshop plan:

  7. Introduction to R & RStudio

  • What’s R
  • What’s RStudio
  • Why R
  • Demo of R
  1. RStudio Overview
  • RStudio Panes
  • RStudio Toolbar
  • RStudio Best Practices
  1. Basics of R Programming
  • Programming Concepts like
    • Variables
    • Data Structures
    • Iteration
    • Control Flows
    • Conditions and more
  1. Data wrangling and Visualization using Tidyverse
  • What’s tidyverse and what does it constitute
  • Data Analysis / Wrangling (mostly tidyr and dplyr)
  • Data Visualiation (ggplot2)
  1. Documentation and Reporting using R Markdown
  • What’s RMarkdown
  • Why RMarkdown
  • Creating Documentation / Reporting
  • Publishing RMarkdown
  1. Sample R Projects
  • Sample R projects (Industry use-case)

    * R and RStudio are required to be installed
    * Basic System Config of 2+ GB RAM, Any OS
    * Some set of packages mentioned in the github repo should be installed
    * Download the github repo that contains data (along with the code and presentation)


Better for those who knew some programming before. But also for Beginners - especially those who want to do Data science.

Speaker bio

Abdul Majed is an Analytics Consultant helping Organizations make sense some out of the massive - often not knowing what to do - data. Married to R (but dating Python). Always amazed by Open Source and its contributors and trying to be one of them.

Organizer @ Bengaluru R user Group (BRUG) Organizer

Contributed to Open source by publishing packages on CRAN and PyPi

Writer @ Towards Data Science and DataScience+



{{ gettext('Login to leave a comment') }}

{{ gettext('Post a comment…') }}
{{ gettext('New comment') }}
{{ formTitle }}

{{ errorMsg }}

{{ gettext('No comments posted yet') }}

Hybrid access (members only)

Hosted by

All about data science and machine learning