Description

Our hands-on sessions will guide you through the intricacies of data visualization using ggplot2, enabling you to create stunning visual representations of your insights. With a focus on efficiency and scalability, we integrate DevOps principles seamlessly into your R workflow, ensuring smooth collaboration, version control, and automated testing. Join us to elevate your proficiency in R, leverage the power of DevOps, and unleash the full potential of data manipulation for transformative insights.

TABLE OF CONTENT

1 . Introduction to R Programming:

A . Overview of R
B . Installation and setup
C . R Studio interface

2 . Basic R Syntax:

A . Variables and data types
B . Operators
C . Control structures (if statements, loops)

3 . Data Structures in R Programming:

A . Vectors
B . Matrices
C . Lists
D . Data frames

4 . Functions in R:

A . Creating functions
B . Built-in functions
C . Passing arguments

5 . Data Import and Export:

A . Reading data from files (CSV, Excel, etc.)
B . Writing data to files

6 . Data Manipulation with dplr:

A  . Introduction to the dplyr Package

B . Basic Data Manipulation Operations

• • Filtering
  • Sorting
  • Summarizing

C .  Advanced Data Manipulation TechniCques:

• Joins
• Grouping

7 . Data Visualisation with ggplot2:

Introduction to the ggplot2 Package:

• Creating Basic Plots:
  • Scatter Plots
  • Bar Plots
  • Line Plots
• Customizing Plots:
  • Themes
  • Colors
  • Annotations

8 . Statistical Analysis in R:

A . Descriptive statistics
B . Inferential statistics
C . Hypothesis testing

9 . R Programming Packages:

A . Installing and loading packages
B . Popular packages for data analysis

10 . Introduction to Shiny:

A . Basics of Shiny web applications
B . Creating interactive dashboards

11 . Version Control with Git and GitHub:

A . Introduction to Git
B . Basic Git commands
C . Collaborative coding with GitHub

12 . Advanced Topics in R Programming:

A . Advanced R Programming Concepts

• • • Functional Programming
    • Vectorization

B . Performance Optimization Techniques

• • • Using data.table for Large Datasets

C . Writing Custom Functions and Packages

Please Visit Rlang.io Official Site:

 Locus Academy has more than a decade experience in delivering the training/staffing on R Programming for Data Manipulation and Visualisation  for corporates across the globe. The participants for the training/staffing on R Programming for Data Manipulation and Visualisation are extremely satisfied and are able to implement the learnings in their on going projects.

Other useful references : 

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