- Integrated Development Environments
- Programming Principles
- Data Manipulation
- Data Import/Export
- Web Scraping
- Jupyter
- Data Analysis
- Data Science
- R Programming
- Data Structures
- Exploratory Data Analysis
Introduction to R Programming for Data Science
Completed by Andreas P Kalogeropoulos
March 23, 2023
11 hours (approximately)
Andreas P Kalogeropoulos'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
