- Programming Principles
- Data Structures
- R Programming
- Data Manipulation
- Jupyter
- Exploratory Data Analysis
- Web Scraping
- Data Science
- Data Analysis
- Data Import/Export
- Integrated Development Environments
Introduction to R Programming for Data Science
Completed by Miguel Ángel Buitrago Zamora
September 12, 2024
10 hours (approximately)
Miguel Ángel Buitrago Zamora's account is verified. Coursera certifies their successful completion of Introduction to R Programming for Data Science
What you will learn
Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks.
Control program flow with conditions and loops, write functions, perform character string operations, write regular expressions, handle errors.
Construct and manipulate R data structures, including vectors, factors, lists, and data frames.
Read, write, and save data files and scrape web pages using R.
Skills you will gain
