R Programming
 
Course Outline

The breakdown below provides an outline of the course content & learning path.

The aim of this training is to give you a quick start in R programming. You will know how to use R for effective data management & data analysis.

in this course, you'll be learning about the basics of R, and you'll end with the confidence to start writing your own R Scripts.

After completing this course, the participants will be able to:

  • Setup your R programming environment.
  • Understand the data structure in R.
  • Write and maintain you own R programs.
  • Able to collect, clean and visualize data for analysis.
  • Rearrange data into an optimal tidy format with the Tidyverse package.
  • Manipulate dates and times in R.
  • Merge and separate different data sets.
  • Explain the differences between the Tidyverse and standard R.

Beginner to Intermediate

4 Days

  • i. Introducing R
  • In this chapter, you will take your first steps with R. You will have a brief introduction of R and get the R environment running on your local computer. You will also learn how to use the console as a calculator and how to assign variables.
  • What is R?
  • Installation of R and RStudio
  • ii. R Data Types
  • In this chapter, you will get to know the basic data types in R, and differentiate each of the data types of R.
  • Number
  • Date and Time
  • Vectors
  • Lists
  • Data Frame
  • Factor
  • Matrix
  • iii. R Programming Fundamentals
  • In this chapter, you will get lean how to create a program in R by using IF Else, For and While loops in R. You will also learn how to create functions and re-use them.
  • Conditions and Loops
  • Functions in R
  • iv. Basic Data Management Operation
  • In this chapter, you will be able to do some data management processes such as checking data quality, cleaning data, recoding data etc.
  • Data manipulation
  • Data cleaning
  • v. Reading and Writing Data
  • In this chapter, you will get to know how to read/import data from excel, text files and remote data sources such databases from the internet using API. You will also learn how to write/export back data to excel, databases etc.
  • vi. Data Visualization
  • In this chapter you will learn how to visualise your data using different types of graphs (histogram, pie chart, bar graph, etc.)
  • vii. Advanced Data Management with Tidyverse Package
  • In this chapter you will learn how to use the Tidyverse Package to deal with data on a day-to-day basis. By focusing on small key tasks, the Tidyverse suite of packages removes the pain of data manipulation. The Tidyverse allows you to import, tidy, transform, manipulate, and visualise data. This course covers key Tidyverse areas, such as dplyr, lubridate, tidyr and tibbles.
  • What is the Tidyverse?
  • Tibbles vs Data Frames: differences and similarities
  • dplyr: filtering, joins, and groups
  • Tidy data: What is it and how to get it using tidyr
  • Dates/times with the lubridate package
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