R Programming for Data Science & Machine Learning – Course Curriculum

1.1. FUNDAMENTALS OF R

• Installation of R & R Studio
• Features of R
• Variables in R
• Constants in R
• Operators in R
• Datatypes and R Objects
• Accepting Input from keyboard
• Important Built-in functions

1.2. VECTORS

• Creating Vectors
• Accessing elements of a Vector
• Operations on Vectors
• Vector Arithmetic

1.3. CONTROL STATEMENTS

• I statement
• if…else statement
• if else() function
• switch() function
• repeat loop
• while loop
• for loop
• break statement
• next statement

1.4. FUNCTIONS IN R

• Formal and Actual arguments
• Named arguments
• Global and local variables
• Argument and lazy evaluation of functions
• Recursive functions

1.5. MATRICES

• Creating matrices
• Accessing elements of a Matrix
• Operations on Matrices
• Matrix transpose

1.6. STRINGS

• Creating strings
• paste() and paste0()
• Formatting numbers and string using format()
• String manipulation

1.7. LISTS

• Creating lists
• Manipulating list elements
• Merging lists
• Converting lists to vectors

1.8. ARRAYS IN R

• Creating arrays
• Accessing array elements
• Calculations across array elements

1.9. R FACTORS

• Understanding factors
• Modifying factors
• Factors in Data frames

1.10. DATA FRAMES IN R

• Creating data frame
• Operations on data frames
• Accessing data frames
• Creating data frames from various sources

1.11. DATA VISUALIZATION IN R

• Need for data visualization
• Bar plot
• Plotting categorical data
• Stacked bar plot
• Histogram
• plot() function and line plot
• pie chart / 3D pie chart
• Scatter plot
• Box plot

1.12. STRINGR PACKAGE

• Important functions in stringr
• Regular expressions

1.13. DPLYR PACKAGE

Everyone

Passion and determination to achieve your goals!