R for Data Science

R is a powerful language for data analysis, data visualization, machine learning, statistics. Originally developed for statistical programming, it is now one of the most popular languages in data science. In this course, you'll be learning about the basics of R, and you'll end with the confidence to start writing your own R scripts.But this isn't your typical textbook introduction to R. You're not just learning about R fundamentals, you'll be using R to solve problems related to movies data. Using a concrete example makes the learning painless. You will learn about the fundamentals of R syntax, including assigning variables and doing simple operations with one of R's most important data structures -- vectors!From vectors, you'll then learn about lists, matrix, arrays and data frames. Then you'll jump into conditional statements, functions, classes and debugging. Once you've covered the basics - you'll learn about reading and writing data in R, whether it's a table format (CSV, Excel) or a text file (.txt). Finally, you'll end with some important functions for character strings and dates in R.

Module 1 - R basics

• Math, Variables, and Strings
• Vectors and Factors
• Vector operations

Module 2 - Data structures in R

• Arrays & Matrices
• Lists
• Dataframes

Module 3 - R programming fundamentals

• Conditions and loops
• Functions in R
• Objects and Classes
• Debugging

Module 4 - Working with data in R

• Reading CSV and Excel Files
• Reading text files
• Writing and saving data objects to file in R

Module 5 - Strings and Dates in R

• String operations in R
• Regular Expressions
• Dates in R