Data Science: NLP and Sentimental Analysis in R

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Caution before taking this course:

This course does not make you expert in R programming rather it will teach you concepts which will be more than enough to be used in machine learning and natural language processing models.

About the course:

In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.

This course covers following topics:

1. R programming concepts: variables, data structures: vector, matrix, list, data frames/ loops/ functions/ dplyr package/ apply() functions

2. Web scraping: How to scrape titles, link and store to the data structures

3. NLP technologies: Bag of Word model, Term Frequency model, Inverse Document Frequency model

4. Sentimental Analysis: Bing and NRC lexicon

5. Text mining

By the end of the course you’ll be in a journey to become Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.

What you’ll learn

  • Use R for Data Science and Machine Learning
  • Provides the entire toolbox you need to become a NLP engineer
  • Learn how to pre-process data
  • Apply your skills to real-life business cases
  • Able to perform web scraping
  • Learn text mining
  • able to perform sentimental analysis on any text


  • No programming experiences required
  • No R programming experience required
  • Machine with any OS (Linux, MacOSX, Windows) and proper internet connection required

Who this course is for:

  • You should take this course if you want to become a Data Scientist or if you want to learn about the field
  • You should take this course if you want to learn text mining and text analysis doing fun projects
  • You should take this course if you want to learn web scraping

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