Requirements
- Enthusiasm and determination to make your mark on the world!
1. Fundamentals of R Language
- Introduction to R
- History of R
- Why R programming Language
- Comparison between R and Python
- Application of R
2. Setup of R Language
- Local Environment setup
- Installing R on Windows
- Installing R on Linux
- RStudio
- What is RStudio?
- Installation of RStudio
- First Program – Hello World
3. Variables and Data Types
- Variables in R
- Declaration of variable
- Variable assignment
- Finding variable
- Data types in R
- Data type conversion
- R programs for Variables and Data types in RStudio
4. Input-Output Features in R
- scan() function
- readline() function
- paste() function
- paste0() function
- cat() function
- R Programs for implementing these functions in RStudio
5. Operators in R
- Arithmetic Operators
- Relational Operators
- Logical Operators
- Assignment Operators
- Miscellaneous Operators
- R Programs to perform various operations using operators in RStudio
6. Data Structure in R (part-I)
- What is data structure?
- Types of data structure
- Vector- What is a vector in R?
– Creating a vector
– Accessing element of vector
– Some more operations on vectors
– R Programs for vectors in RStudio
- Application of Vector in R
- List- What is a list in R?
– Creating a list
– Accessing element of list
– Modifying element of list
– Some more operations on list
- R Programs for list in RStudio
7. Data Structure in R (part-II)
- Matrix or Matrices- What is matrix in R?
– Creating a matrix
– Accessing element of matrix
– Modifying element of matrix
– Matrix Operations
- R Programs for matrices in RStudio
- Application of Matrices in R
- Arrays- What are arrays in R?
– Creating an array
– Naming rows and columns
– Accessing element of an array
– Some more operations on arrays
- R Programs for arrays in RStudio
8. Data Structure in R (part-III)
- Data frame- What is a data frame in R?
– Creating a data frame
– Accessing element of data frame
– Modifying element of data frame
– Add the new element or component in data frame
– Deleting element of data frame
– Some more operations on data frame
- R Programs for data frame in RStudio
- Factors- Factors in R
– Creating a factor
– Accessing element of factor
– Modifying element of factor
- R Programs for Factors in RStudio
- Application of Factors in R
9. Decision Making in R
- Introduction to Decision making
- Types of decision-making statements
- Introduction, syntax, flowchart and programs for- if statement
– if…else statement
– if…else if…else statement
– switch statement
10. Loop control in R
- Introduction to loops in R
- Types of loops in R- for loop
– while loop
– repeat loop
– nested loop
- break and next statement in R
- Introduction, syntax, flowchart and programs for- for loop
– while loop
– repeat loop
– nested loop
11. Functions in R
- Introduction to function in R
- Built-in Function
- User-defined Function
- Creating a Function
- Function Components
- Calling a Function
- Recursive Function
- Various programs for functions in RStudio
12. Strings in R
- Introduction to string in R- Rules to write R Strings
– Concatenate two or more strings in R
– Find length of String in R
– Extract Substring from a String in R
– Changing the case i.e. Upper to lower case and lower to upper case
- Various programs for String in RStudio
13. Packages in R
- Introduction to Packages in R
- Get the list of all the packages installed in RStudio
- Installation of the packages
- How to use the packages in R
- Useful R Packages for Data Science
- R program for package in RStudio
14. Data and File Management in R
- Getting and Setting the Working Directory
- Input as CSV File
- Analysing the CSV File
- Writing into a CSV File
- R programs to implement CSV file
15. Plotting in R (Part-I)
- Line graph
- Scatterplots
- Pie Charts
- 3D Pie Chart
16. Plotting in R (Part-II)
- Bar / line chart
- Histogram
- Box plot
- R Developers & Data Developers
- Data Scientists – R, Python
- Newbies and beginners aspiring for a career in programming & statistical analysis
- Data Engineers and Statistical Analysts
- R & Python Programmers
- Technical & Analytics Consultants
- Anyone wishing to learn data science and machine learning
- Lead R Developers
- R Modelling Analysts
- Data Software Developers
- Financial and Marketing Analysts
- Software Engineers
- Web Application Developers
- Business Analysts and Consultants
- Data Science and Machine Learning enthusiasts