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Text Mining in R

Updated 03/2026
Discover text mining in R and learn how to extract exciting insights from tweets, product reviews, and books through sentiment analysis in R.
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RData Manipulation16 hr7,572

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Track Description

Text Mining in R

Discover text mining in R and learn how to extract exciting insights from tweets, product reviews, and books through sentiment analysis in R.You’ll discover a range of approaches to organizing and analyzing text data from books, articles, documents, and more. You’ll get a primer into regular expressions and look at ways to search for common patterns in text effectively.As you progress, you’ll cover a range of tidyverse packages that can help with text analysis in R, including stringr and tidytext. As well as covering string manipulation and the bag of words technique for text mining in R, you’ll also look at how sentiment analysis works.By the time you finish, you’ll have a firm understanding of text analysis in R and will have the confidence to carry out your own text mining and sentiment analysis.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Text Analysis in R

    Analyze text data in R using the tidy framework.

  • Course

    4

    Sentiment Analysis in R

    Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Text Mining in R
4 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, this track is suitable for beginners. It's designed to introduce users to the fundamentals of text mining and sentiment analysis in R so that they can continue to gain domain-specific expertise.

What is the programming language of this Track?

This Track is written in R, an open-source programming language and software environment for statistical computing and graphics.

Which jobs will benefit from this Track?

This Track is geared towards preparing aspiring data scientists, statisticians, and analysts for jobs involving text mining and sentiment analysis. It can also benefit data visualization specialists, web developers, digital marketers, UX and UI designers, business strategy planners, and more.

How will this Track prepare me for my career?

This Track will equip you with the necessary technical skills and knowledge to perform text mining and sentiment analysis in R. Additionally, it will help you understand the common patterns in text data, giving you a big advantage for your career.

How long does it take to complete this Track?

This track should take approximately 16 hours to complete, as it consists of several courses that significantly upskill users.

What's the difference between a skill track and a career track?

A skill track is focused on the fundamental concepts and techniques related to a particular topic or domain. It is designed to help users gain domain-specific expertise. On the other hand, a career track is geared towards preparing users for a particular job role. It focuses on the practical skills and aptitudes needed to succeed in the job and the industry.

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