## Offered By: IBM

# 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.

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Course

R Programming

12.1k+ Enrolled# At a Glance

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.

You'll then learn about lists, matrices, arrays and data frames from vectors. 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 Syllabus**

**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

**General Information**

- 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**

- None

**Requirements**

- None

Estimated Effort

6 Hours

Level

Beginner

Skills You Will Learn

Data Science, Data Visualization, Machine Learning, Data Analysis

Language

English