Do You Want To Learn R ?

Dear R users,

If you prefer to learn R with video, we have compiled a list of basic R tutorials that will show your way through R from scratch. The content of this course is thought through in great detail, giving due consideration to essential concepts that beginners must be introduced to.  Eventually, we refined the content over and over until we got a balanced content that is not too verbose, yet succeeds in delivering the core of concepts. This is structured to overcome the common roadblocks our students and non-programmer colleagues faced so that the doubts and questions you have gets addressed at some point during the course. So take this course completely end to end, Twice if possible.

The videos are of decent quality and the explanations are straight forward making it very easy for beginners to grasp. The best part is this course is absolutely FREE. So dont waste your time anymore looking for ‘The Course’ because this is it. Lets get to action.
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R Tutorials For Beginners (from scratch)

Time to complete: 2 Hours 18 min

Intended Audience: Beginners using R, Non-programmer Data scientists.

  1. Installing R
  2. R’s Interface – How to get your way around R
  3. Basic Math Operations
  4. Variables and Data Types
  5. Introduction to Vectors
  6. Set up your work directory.. et al
  7. Create special vector sequences – part 1
  8. Create special vector sequences – part 2
  9. Random Numbers
  10. More on vectors + find and remove missing values
  11. Get specific items from vector using ‘which’ operator
  12. Converting one variable type to another
  13. Introduction to Lists
  14. Set operations – part 1
  15. Set operations – part 2
  16. Special conditionals and common mistakes with If-Else statements
  17. For-Loops
  18. Dataframes – part 1
  19. Dataframes – part 2
  20. Getting specific items in dataframes using which()
  21. Binning data
  22. Counts tables – part 1
  23. Counts tables – part 2
  24. Read and write data – part 1/3
  25. Read and write data – part 2/3
  26. Read and write data – improving import efficiency – part 3/3
  27. Built-in dataframes
  28. More useful dataframes operations
  29. Practice exercise 1 (with solutions)
  30. Practice exercise 2 (with solutions)
  31. Practice exercise 3 (with solutions)
  32. Dates
  33. Practice exercise 4 (dates)
  34. Dates operations with R (POSIXlt)
  35. Writing functions
  36. Tips to write neat and awesome functions
  37. Debugging code (Comprehensive)

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