R Programming:For Data Science With Real Exercises

This course will  introduces the R statistical processing language, including how to install R on your computer, read data from SPSS and spreadsheets, and use packages for advanced R functions. The course continues with examples on how to create charts and plots, check statistical assumptions and the reliability of your data, look for data outliers, and use other data analysis tools. Finally, learn how to get charts and tables out of R and share your results with presentations and web pages.

The following topics are include

·         What is R?

·         Installing R and R studio (IDE)

·         Creating bar character for categorical variables

·         Building histograms

·         Calculating frequencies and descriptive

·         Computing new variables

·         Creating scatter plots

·         Comparing means

R language basics commands

Reading ,Accessing and Summarizing Data in R

Quick Install R language on UBUNTU Linux

R Programming For Data Science refers to the use of the R programming language and associated tools for tasks related to data science. R is a popular open-source programming language and environment specifically designed for statistical computing and graphics. It provides a wide range of functionalities and packages tailored for data analysis, visualization, and machine learning. Overall R is a powerful and versatile programming language for data science, offering a comprehensive suite of tools and resources for data analysis, visualization, and machine learning tasks. Whether you're a beginner or an experienced data scientist, R can be an invaluable tool in your toolkit for working with data.