Introduction to R (Basics to Intermediate Advanced)

Characteristics

R is a very popular, open-source environment for statistical computing, data analysis, and graphics creation. This course introduces participants to the R programming language. It covers the basics of the language, libraries, and advanced concepts.

This instructor-led training, delivered live (online or onsite), is aimed at beginner data analysts who want to use R programming for data manipulation, performing basic data analysis, and creating attractive visualizations to derive insights.

Upon completion of the course, participants will be able to:

• Understand the basics of programming in R.
• Apply fundamental data science processes.
• Create visual representations of data.

Course Format

• Interactive lectures and discussions.
• Plenty of exercises and practice.
• Practical implementation in a live-lab environment.

Requirements

Basic programming experience is recommended.

Target Group

Data Analysts.

Course Introduction

About Data Science

• Definition of data science
• The data science process.

Introduction to the R Language

Variables and Types

Control Structures (Loops / Conditions)

Scalars, Vectors, and Matrices in R

• Defining vectors in R
• Matrices

Text and String Manipulation

• Character data type
• File input/output

Lists

Functions

• Introduction to functions
• Closures
• lapply/sapply functions

DataFrames

Labs for all sections

DataFrames and File Input/Output

Reading Data from Files

Data Preparation

Built-in Datasets

Visualization

• Graphics package
• plot() / barplot() / hist() / boxplot() / scatter plot
• Heatmap
• ggplot2 package (qplot(), ggplot())

Exploration with Dplyr

Labs for all sections