Coding in R for Data
offered by New York University

Private University
Estd. 1831

Coding in R for Data
at
New York University
Overview

Build apps, create reports, and deliver presentations of your data in R.

Duration	4 weeks
Total fee	₹64,526
Mode of learning	Online
Course Level	UG Certificate

Coding in R for Data

Table of content

Overview
Highlights
Course Details
Curriculum
Faculty

Coding in R for Data
at
New York University
Highlights

Earn a certificate of completion from Nyu

Coding in R for Data
at
New York University
Course details

Skills you will learn

Data structures R Statistics Data visualization

What are the course deliverables?

R Programming Basics
Preparing Data in R
Report & Present Data in R

More about this course

In today's age of analytics, the ability to transform data into information and actionable insights is essential
Coding in R for Data provides students with an understanding of how to import, format, understand, and communicate their data findings in R, a common statistical language utilized in a diverse range of industries
Learn how to program in R for effective data manipulation and visualization
Program participation will also develop the ability to create control structures, such as loops and conditional statements to traverse, sort, merge, and evaluate data

Coding in R for Data
at
New York University
Curriculum

Week 1: Coding Basics

Introduction to R Programming

Data Structures, Variables, and Data Types

Week 2 Data Exploration

Packages, Scripts, and Rmarkdown

Descriptive Statistics in R

Week 3 Data Presentation

Reporting and Visualization in Rmarkdown

Data Cleaning and Formatting for Messy Data

Week 4 Data Application

Functions, Iterations, and Conditionals

Interactive Applications Using Rshiny

Coding in R for Data
at
New York University
Faculty details

Kristen Sosulski

Kristen Sosulski is the author of the award winning business reference, Data Visualization Made Simple: Insights into Becoming Visual. For the past twenty years, Kristen has been working at the intersection of learning science, technology, and business.