IBM: R Programming Basics for Data Science

91,00 

This course introduces you to R language fundamentals and covers common data structures, programming techniques, and how to manipulate data all with the help of the R programming language.

Categories ,

91,00 

This course introduces you to R language fundamentals and covers common data structures, programming techniques, and how to manipulate data all with the help of the R programming language.

Categories ,

Discover the Course

About this course.

The R language plays a critical role in data analysis and a common programming language when working in the field of data science & analytics. This course will introduce you to R language fundamentals like data types, techniques for manipulation, and how to implement fundamental programming tasks. We’ll also cover common data structures, programming fundamentals and how to manipulate data all with the help of the R programming language.

This course emphasizes hands-on and practical learning. You will write a simple program using RStudio, manipulate data in a data frame or matrix, and complete a final project as a data analyst using Watson Studio and Jupyter notebooks to produce data-driven insights.

No prior knowledge of R, or programming is required.

At a glance

  • Institution: IBM
  • Subject: Data Analysis & Statistics
  • Level: Introductory
  • Prerequisites:
    None
  • Language: English
  • Video Transcript: English
  • Associated programs:
    • Professional Certificate in Data Analytics and Visualization with Excel and R
    • Professional Certificate in Applied Data Science with R
  • Associated skills:RStudio, Data Analysis, Watson Studio, Jupyter, Data Science, Data Structures, R (Programming Language)

What you’ll learn

  • Manipulate numeric and textual data types using the R programming language and RStudio or Jupyter Notebooks.
  • Define and manipulate R data structures, including vectors, factors, lists, and data frames.
  • Control program flow, define functions, perform character string and date operations, define regular expressions, and handle errors.
  • Read, write, and save data files and scrape web pages using R.

Course Overview

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