DataCamp
FreeIntroduction to Natural Language Processing in R
4.8(40)8k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate course equips R practitioners with essential natural language processing tools. Through practical examples, it covers core text mining methodologies—from pattern matching with regular expressions to advanced topic modeling and named entity recognition—preparing analysts for complex textual data projects.
Who It's For
R programmers, data analysts, and researchers seeking to analyze, classify, and uncover hidden patterns within textual datasets.
Key Takeaways
- Regular Expressions: Master regular expressions in R for precise string matching, parsing, and text cleaning.
- Topic Modeling: Uncover latent themes and structures across large document collections using topic models.
- Named Entity Recognition: Identify and extract entities such as names, dates, and locations from unstructured text.
- Practical Workflows: Build reusable R scripts to kickstart future text analytics and NLP projects.
About this course
As with any fundamentals course, Introduction to Natural Language Processing in R is designed to equip you with the necessary tools to begin your adventures in analyzing text. Natural language processing (NLP) is a constantly growing field in data science, with some very exciting advancements over the last decade. This course will cover the basics of these topics and prepare you for expanding your analysis capabilities. We dive into regular expressions, topic modeling, named entity recognition, and others, all while providing thorough examples that can be used to kick start your future analysis.
Price
Free
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