R Programming Fundamentals

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R Programming Fundamentals
at
edX
Overview

Equip with the essential skills needed to effectively utilize the R programming language for data analysis, statistical computing, and data visualization

Duration	6 weeks
Start from	Start Now
Total fee	₹8,269
Mode of learning	Online
Official Website	Go to Website
Credential	Certificate

R Programming Fundamentals
at
edX
Highlights

Earn a certificate after completion of the course
Access to course materials
Graded assignments for practice

R Programming Fundamentals
at
edX
Course details

Who should do this course?

Employees in fields such as finance, marketing, healthcare, and more, who seek to enhance their data analysis skills

Individuals with a keen interest in learning data analysis and visualization techniques using R

What are the course deliverables?

To introduce the R programming language and its environment

To teach fundamental programming concepts using R

To enable participants to perform data manipulation and analysis

To provide skills for creating data visualizations and interpreting results

To prepare participants for more advanced studies in data science and analytics

More about this course

This course covers the basics of R: a free programming language and software environment used for statistical computing and graphics. R is widely used by data analysts, statisticians, and data scientists around the world. This course covers an introduction to R, from installation to basic statistical functions. You will learn to work with variable and external data sets, write functions, and hear from one of the co-creators of the R language, Robert Gentleman

R Programming Fundamentals
at
edX
Curriculum

How to download and install R.

How to use R in an interactive and easy-to-understand environment.

What the key objects are and how we manipulate them in R.

Where the objects are stored and how to save our work.

All the important data structures: data frames, lists, matrices.

How to import data into R and how to save your work.

How to manipulate and preprocess data and work with missing values.

How to plot your data – an introduction to ggplot2.

How to use the wealth of contributed packages to achieve a specific task.

R Programming Fundamentals
at
edX
Faculty details

Susan Holmes

Trained in the French school of Data Analysis in Montpellier, Susan Holmes has been working in non parametric multivariate statistics applied to Biology since 1985. She has taught at MIT, Harvard and was an Associate Professor of Biometry at Cornell before moving to Stanford in 1998.