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Learner Reviews & Feedback for Introduction to Text Mining with R by HSE University

About the Course

This course gives you access to the text mining techniques that are used by top data scientists from all over the world. Since most information available online in the form of text, knowing when and how to use these techniques, algorithms and models will not only give you an edge over your competition in the job market, but also allow you to see the world around you from a completely new perspective. This course covers from the very basics of programmatically working with text to advanced unsupervised learning methods. The course is taught using the R programming language, and starts with a brief introduction to the language itself (and RStudio, the primary IDE used for R programming), together with a short introduction to Tidyverse, a commonly used set of R libraries. Then, text preprocessing techniques and supervised learning methods will be introduced. The final part of the course covers various unsupervised learning methods that can be used for analysis of textual data. Students are required to complete quizzes (1-2 for each of the 4 weeks) and to complete a final project using open data and the knowledge they gained during the course. They are designed to illustrate some of the specific state-of-the-art approaches within the broader areas. This Course is part of HSE University Master of Data and Network Analytics degree program. Learn more about admission into the program and how your Coursera work can be leveraged if accepted into the program here
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