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.

Outline

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

8. RStudio Overview
   * RStudio Panes
   * RStudio Toolbar
   * RStudio Best Practices
9. Basics of R Programming
   * Programming Concepts like
   • Variables
   • Data Structures
   • Iteration
   • Control Flows
   • Conditions and more
10. Data wrangling and Visualization using Tidyverse
    * What’s tidyverse and what does it constitute
    * Data Analysis / Wrangling (mostly tidyr and dplyr)
    * Data Visualiation (ggplot2)
11. Documentation and Reporting using R Markdown
    * What’s RMarkdown
    * Why RMarkdown
    * Creating Documentation / Reporting
    * Publishing RMarkdown

12. Sample R Projects
    * Sample R projects (Industry use-case)

    Requirements.
    * 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)

Requirements

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+

Links

• https://towardsdatascience.com/@amrwrites
• https://github.com/amrrs
• https://kaggle.com/nulldata/kernels

Slides

https://amrrs.github.io/r_beginners_workshop/presentation.html#1