R Tutorial : Beginner to Advanced

R Tutorial for Beginners and Advanced Users
R language is the world's most widely used programming language for statistical analysis and predictive modeling. It's popularity is claimed in many recent surveys and studies. In a study of skills associated with LinkedIn profiles by RJmetrics , "R" was the most associated skill with data scientists in a category of software. In a recent Dice Tech Salary Survey, it was found people who know R programming language fetch more salary than python and SAS programmers.

R Tutorials for Beginners to Advanced Users

The R language tutorials are listed below which are ideal for beginners to advanced users.

R Tutorial

The following R language tutorial are designed for beginners who have no programming background or new to R programming language. These tutorials cover how to get started with R, importing and exporting data, data exploration and manipulation, report generation etc.
  1. Companies using R
  2. Getting Started with R
  3. Data Types (Structures) in R
  4. Create Sample (Dummy) Data in R 
  5. Importing Data into R 
  6. Exporting Data in R
  7. Copy Data from Excel to R
  8. Loading and Saving Data with R
  9. Data Exploration with R
  10. Data Manipulation with R
  11. Data Manipulation with dplyr package
  12. Data Manipulation with data.table package
  13. If Else and Nested If Else in R
  14. Transpose Data with R
  15. Loops with R
  16. Error Handling in R
  17. Converting a factor to integer
  18. Character Functions
  19. Apply Function on Rows
  20. Keep / Drop Columns with R
  21. Joining and Merging with R
  22. Summarize Data with R
  23. Indexing Operators in List
  24. Split a data frame
  25. Convert data from wide to long format
  26. R Which Function Explained
  27. How to Update R Software
  28. Convert Backslash File Path to Forward Slash
  29. Send Email From R
  30. Run SQL Queries in R
  31. Measuring Execution Time of R Code
  32. Install an archived package
  33. Delete columns where certain % of missing values
  34. Converting multiple numeric variables to factor
  35. Extracting Numeric and Factor Variables
  36. Install R package from GitHub account
  37. Password Generator App with R
  38. Reading large CSV Files
  39. Creating Dummy Columns From Categorical Variables
  40. Convert Categorical Variables to Numeric
  41. CARET Package [Part I]
  42. CARET Package [Part II]
  43. Create Wordcloud with R

Data Science with R Tutorials
These tutorials aimed at people who want to build a career in predictive modeling and data science. These tutorials cover various data mining, machine learning and statistical techniques with R. It includes tutorials on performing descriptive and inferential statistics, linear and logistic regression, time series, variable selection and dimensionality reduction, classification, market basket analysis, random forest, ensemble technique, clustering and more.
  1. Linear Regression with R
  2. Logistic Regression with R
  3. Cluster Analysis with R
  4. Validate Cluster Analysis
  5. Decision Tree on Credit Data
  6. Random Forest Explained
  7. Gradient Boosting Model (GBM) with R
  8. Support Vector Machine (SVM) in R
  9. Market Basket Analysis
  10. ARIMA Modeling with R
  11. Dimensionality Reduction with R
  12. Correcting Collinearity with R
  13. Weighting in Decision Tree and SVM
  14. Decision Tree : Custom CTREE Plot
  15. Train Random Forest with CARET package
  16. Missing Value Imputation with Random Forest
  17. Speeding up Random Forest with R
  18. Variable Selection / Reduction with R
  19. Variable Selection - Wald Chi Square
  20. Predicting Transformed Dependent Variable
  21. Ensemble Learning : Stacking (Blending)
  22. Parallelizing Machine Learning Algorithms
  23. Ways to correct Class Imbalances / Rare Events
  24. Missing Imputation with Mice Package
  25. Predict Functions in R
  26. Splitting Data into Training and Validation Datasets
  27. R Function : Gain and Lift Table
  28. Automatically Create Model Formula
  29. Calculating AUC of Training Dataset 
  30. R Functions : AUC and KS Statistics
  31. Two ways to train a model with R

Text Mining with R
These tutorials would help you to understand the basics of text mining with R. It includes tutorials on creating word cloud by demographics and sentiment analysis with R, 

R Interview Questions and Answers
This tutorial helps you to prepare for interview for R programmers and data scientists roles.  R Interview Questions

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