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.
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Introduction to R & RStudio
-
RStudio Overview
-
Basics of R Programming
-
Data wrangling and Visualization using Tidyverse
-
Documentation and Reporting using R Markdown
-
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:
-
Introduction to R & RStudio
- What’s R
- What’s RStudio
- Why R
- Demo of R
- RStudio Overview
- RStudio Panes
- RStudio Toolbar
- RStudio Best Practices
- Basics of R Programming
- Programming Concepts like
- Variables
- Data Structures
- Iteration
- Control Flows
- Conditions and more
- Data wrangling and Visualization using Tidyverse
- What’s tidyverse and what does it constitute
- Data Analysis / Wrangling (mostly
tidyr
and dplyr
)
- Data Visualiation (
ggplot2
)
- Documentation and Reporting using R Markdown
- What’s
RMarkdown
- Why
RMarkdown
- Creating Documentation / Reporting
- Publishing RMarkdown
- 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)
Better for those who knew some programming before. But also for Beginners - especially those who want to do Data science.
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+
https://amrrs.github.io/r_beginners_workshop/presentation.html#1
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