Introductory R (Basic to Intermediate)

Overview

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

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

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

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

Course Format

• Interactive lecture and discussion.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Prerequisites

Basic programming experience recommended.

Target audience

Data analysts.

Introduction to the course

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