- 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 SAI RAGHAVENDRA SUBHASH NALAM
January 4, 2025
11 hours (approximately)
SAI RAGHAVENDRA SUBHASH NALAM'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
