We offer this course to make you learn how to program in R and how to use R for effective data analysis. R Programming is a powerful statistical the programming language which is used for Predictive Modeling and other data mining related techniques.R programming language is one the most powerful tool for computational statistics, visualization and data science.
The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.
R programming can be used for data manipulation, data aggregation, statistical Modelling, Creating charts and plots. R programming is becoming the most necessary skill in the field of analytics for its open source credibility.
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Prerequisites:
R Programming can be learned by anyone. No prior Programming skills required. Even Non-Engineers can learn R programming. Statistical Knowledge will be added advantage
Course Objectives:
After the course, you will be able to:
- Understand Syntax of R language
- Understand Programming Fundamentals of R language
- Understand the Data Manipulation
- Create Visualizations and Plots
- Understand the Concepts of Vector and Data Types
- Understand Functions used in R Programming
Course Contents
- Types of variables
- Using Variables
- Arithmetic Operators
- Relational Operators
- Logical Operators
- Assignment Operators
- Miscellaneous Operators
- Arrays
- Factors
- Data Frames
- If Statement
- If...Else Statement
- Repeat Loop
- While Loop
- For Loop
- Break Statement
- Next Statement
- Function Definition
- Function Components
- Built-in Function
- User-defined Function
- Calling a Function
- Install a New Package
- Install Directly from CRAN
- Install Package Manually
- Load Package to Library
- Check Available R Packages
- Get the list of all the packages installed
- Joining Columns and Rows in a Data Frame
- Merging Data Frames
- Melting and Casting
- Melt the Data
- Cast the Molten Data
- CSV Files
- Excel Files
- Binary Files
- XML Files
- Web Data
- Database
- Pie Charts
- Bar Charts
- Boxplots
- Histograms
- Line Graphs
- Scatterplots
- Mean, Median & Mode
- Linear Regression
- Multiple Regression
- Logistic Regression
- Normal Distribution
- Binomial Distribution
- Poisson Regression
- Analysis of Covariance
- Time Series Analysis
- Nonlinear Least Square
- Decision Tree
- Random Forest
- Survival Analysis
- Chi Square Tests