- Web Scraping
- Data Analysis
- Jupyter
- Exploratory Data Analysis
- Data Science
- Data Manipulation
- Programming Principles
- Integrated Development Environments
- Data Structures
- Data Import/Export
- R Programming
Introduction to R Programming for Data Science
Completed by CHRISTOPHER CHARLES-ANDRE BELIZAIRE ROBEANTS
November 1, 2024
10 hours (approximately)
CHRISTOPHER CHARLES-ANDRE BELIZAIRE ROBEANTS'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
