Data Science: NLP and Sentimental Analysis in R

This practical R programming course equips you with the essential skills to excel in data analysis, data visualization, and machine learning. While this course won't make you an R expert, it provides a strong foundation with concepts directly applicable to building powerful machine learning models and natural language processing (NLP) applications.

Get hands-on experience learning how to program in R and leverage its capabilities for effective data manipulation and insightful reporting. We'll guide you through the installation and configuration of the necessary software to create a robust statistical programming environment. You'll understand core programming concepts as they are implemented within the R language.

Our primary goal is to empower you to become a confident Data Scientist with R and secure your first job in the field. This course goes beyond just understanding the syntax; it focuses on practical application and career readiness.

Here's a detailed look at what you'll learn:

• R Programming Fundamentals: Master essential R programming concepts, including variables, data structures like vectors, matrices, lists, and data frames. You'll also learn about loops, functions, the powerful dplyr package, and the apply() functions for efficient data manipulation.
• Web Scraping: Discover how to effectively scrape data from the web, extracting titles, links, and storing them in suitable data structures for further analysis.
• Natural Language Processing (NLP): Explore fundamental NLP technologies, including the Bag of Words model, Term Frequency-Inverse Document Frequency (TF-IDF) model, and their applications in text analysis.
• Sentiment Analysis: Learn to perform sentiment analysis using the Bing and NRC lexicons to understand the emotional tone of text data.
• Text Mining: Develop skills in text mining techniques to extract valuable insights from textual data.

By the end of this course, you'll be well on your way to a career as a Data Scientist using R. You'll gain the confidence and practical skills to apply for jobs and demonstrate your knowledge with real-world projects. Invest in your future and build a solid foundation for a successful career in data science with R.