Course Description

R Programming Tutorial: An In-depth Guide to Data Analysis and Visualization If you're looking to gain proficiency in one of the most widely used statistical programming languages in the world, this R Programming Tutorial is the perfect place to start. Whether you're a beginner who wants to learn the basics or an experienced programmer looking to take your skills to the next level, this comprehensive course will provide you with the knowledge and tools you need to become proficient in R. The course begins by introducing you to the R language and its various data structures and functions. You'll learn how to install and configure R on your computer, and how to use the RStudio integrated development environment to write, debug, and execute R code. From there, the course delves into the various data types and structures that are commonly used in R, including vectors, matrices, arrays, lists, and data frames. You'll learn how to manipulate and transform data using a variety of functions and operators, and how to import and export data from different sources, such as CSV files, Excel spreadsheets, and databases. As you progress through the course, you'll explore more advanced topics, such as data visualization, statistical analysis, and machine learning. You'll learn how to create stunning visualizations using popular packages like ggplot2 and lattice, and how to perform statistical analysis on your data using functions like t-tests, ANOVA, and regression analysis. You'll also get an introduction to machine learning techniques like decision trees, random forests, and neural networks, and learn how to use popular packages like caret and tensorflow to build and evaluate predictive models. Throughout the course, you'll work on real-world examples and projects that will give you hands-on experience with the concepts and techniques covered. By the end of the course, you'll have a solid foundation in R programming and be ready to tackle your own data analysis and visualization projects with confidence. Author: Barton Poulson (freeCodeCamp)