R for Data Science
Are you ready to dive head-first into R? In just a few hours you'll learn how to write your own R code, learn about data structures and create your own functions. You’ll even be able to import data and do some operations. Try our hands-on exercises as we guide your first steps into your data science journey with R.Continue reading
R Programming3.9k+ Enrolled
At a Glance
Are you ready to dive head-first into R? In just a few hours you'll learn how to write your own R code, learn about data structures and create your own functions. You’ll even be able to import data and do some operations. Try our hands-on exercises as we guide your first steps into your data science journey with R.
About This Course
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.
Course SyllabusModule 1 - R basics
- Math, Variables, and Strings
- Vectors and Factors
- Vector operations
- Arrays & Matrices
- Conditions and loops
- Functions in R
- Objects and Classes
- Reading CSV and Excel Files
- Reading text files
- Writing and saving data objects to file in R
- String operations in R
- Regular Expressions
- Dates in R
- This course is self-paced.
- It can be taken at any time.
- It can be audited as many times as you wish.
Recommended skills prior to taking this course
Polong LinPolong Lin is a Data Scientist at IBM in Canada. Under the Emerging Technologies division, Polong is responsible for educating the next generation of data scientists through BDU. Polong is a regular speaker in conferences and meetups, and holds a M.Sc. in Cognitive Psychology.
BDU Course Development TeamThanks to BDU course developement team, BDU interns and all individuals contributed to the development of this course: Helly Patel , Mandeep Kaur , Hiten Patel , Marta Aghili , Anita Vincent , Iqbal Singh , Rishabh jain , Aditya Walia , Kumar Gaurav