## R – PROGRAMMING (35 Hrs.)

### R Language

• Getting R
• R Version
• 32-bit versus 64-bit
• Installing
• The R Environment
• Command Line Interface
• RStudio
• R Packages
• Installing Packages
• Basics of R
• Basic Math
• Variables
• Data Types
• Vectors
• Calling Functions
• Function Documentation
• Missing Data
• Data.frames
• Lists
• Matrices
•  Arrays
• Factors
• Excel Data
• Clipboard
• Control Statements
• if and else
• switch
• ifelse
• Compound Tests
• Loops
• for Loops
• while Loops
• Controlling Loops
• Group Manipulation
• Apply Family
• aggregate
• Data Reshaping
• cbind and rbind
• Joins
• Reshape2
• String Theory
• paste
• sprintf
• Extracting Text
• Regular Expressions
• Graphs with R and GGPlot2
• Basic and Interactive Plots
• Dendrograms
• Pie Chart and Its Alternatives
• Visualizing Continuous Data
• Basic Statistics
• Summary Statistics
• Correlation and Covariance
• T-Tests
• ANOVA
• Probability Distributions
• Normal Distribution
• Binomial Distribution
• Poisson Distribution
• Statistical Methods & Machine Learning Algorithms
• Descriptive statistics and Inferential statistics– R Code

1.1 Linear Regression – Theory
1.2 Linear Regression – R Code
2.1 Logistic Regression – Theory
2.2 Logistic Regression – R Code
3.1 Market Basket Analysis – Theory
3.1 Market Basket Analysis – R Code
4.1 Naive Bayes – Theory
4.1 Naive Bayes – R Code
5.1 Neural Network – Theory
5.1 Neural Network – R Code
6.1 Principal Component Analysis – Theory
6.2 Principal Component Analysis – R Code
7.1 Time Series Analysis – Theory
7.2 Time Series Analysis – R Code
8.1 Unsupervised learning: Clustering – Theory
8.2 Unsupervised learning: Clustering – R Code
9.1 Decision Trees – Theory
9.2 Decision Trees – R Code
10.1 K Nearest Neighbors (kNN) – Theory
10.2 K Nearest Neighbors (kNN) – R Code

• Case Study
• Resume preparation
• Interview Questions/Tips
• Approach to Interview/ How to follow up
• Exclusively doubts clarification on every week end.
• Guiding in Real time