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How I Learn R

A summary of my strategy of picking up R in my university time.

When I was studying in the university, I learnt R programming to complete my final year project, Text Sentiment Analysis and Topic Modeling. It was a nightmare for me as the tasks were not as easy as I thought, especially for someone without strong foundation in data science programming languages (e.g. R, Python).

For a complete beginner, there are plenty of resources you could easily find to pick up a new programming language. Bad new is sometimes there are too much resources that I just could not make up my mind to just choose one. After more than one year of dealing with R (haha), I thought I should share some of my tips in learning R for data analysis.

1. Read Books For a complete beginner like me, going through Hands-On Programming with R is super useful for me! It strengthens my understanding on how R works and how to write a more “R-slang”-like code. Even though the book is lengthy, it is well structured and written. The programming concepts I learned from this book also build my foundation well that I could easily pick up Python when I started working. A KIND Reminder: “Don’t skip the hands-on session” - This is where you can put theory into practice.

2. Writing Notes

Personally, I find writing notes in a my notebook is a great way to learn R. Things that I would jot down in my notebook are:

  • Concepts that I would take more time to digest
  • Solution(s) related to an specific issue/ topic that I find useful _(Usually these will be the solution I found online or written by me)

3. Google Search

Learn how to debug your error by looking for solution on Google. Site such as StackOverFlow, are some of the sites that I visited very frequent when I am coding R.

Pretty simple tips! Be determined and consistent & you will be a R-Master in no time!

Happy Learning R!

Licensed under CC BY-NC-SA 4.0
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