The Fifth Elephant 2019

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Introduction to R for Data Science [Workshop]

Submitted by \AbdulMajedRaja (@amrrs) on Monday, 15 April 2019

Session type: Workshop

Abstract

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

Slides

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

Comments

  • \AbdulMajedRaja (@amrrs) Proposer 3 months ago

    Just wanted to let you know that there are slides in it.

  • Zainab Bawa (@zainabbawa) Reviewer 3 months ago

    Hello Abdul,

    Edit this proposal and resubmit with the following details:

    1. Duration of the workshop. If you are unsure about the exact duration, you can speculatively put it down as either 4 hours or 6 hours for now.
    2. Background knowledge required to participate in the workshop. What concepts/technologies should participants be familiar with in order to attend the workshop.
    3. Target audience: who should attend the workshop? Specify personas rather than mentioning beginner or advanced level audiences. Ensure that the workshop caters to one specific audience segment only.
    4. Who should NOT attend this workshop.
    5. Why attend this workshop? What will participants learn from attending this workshop? How will they benefit?
    6. Detailed workshop plan. Give us a break-up of the different sections of the workshop and what content will be covered in each section.
    7. Requirements. What software and other tech should participants install on their laptops before coming to this workshop? Should participants carry laptops with specific configurations on their machines?

    The above details should be added to this proposal by or before 26 May so that we can review the details and close on the decision.

    • \AbdulMajedRaja (@amrrs) Proposer 2 months ago

      Hello Zainab, Edited the Proposal with the details. Same here:

      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)

    • \AbdulMajedRaja (@amrrs) Proposer 2 months ago

      If in case, You feel this is basic, Please let me know I can move this up in the value chain to start with Data Analysis and end with ML or a niche segment like NLP or Deep Learning.

      • \AbdulMajedRaja (@amrrs) Proposer 2 months ago

        And I’ve conducted this workshop in multiple places - Few Universities, With an organization called Devopedia (@ Microsoft - Jan 2019)

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