R courses can help you learn data manipulation, statistical analysis, data visualization, and programming fundamentals. You can build skills in creating reproducible research, performing regression analysis, and implementing machine learning algorithms. Many courses introduce tools like RStudio and packages such as ggplot2 and dplyr, which enhance your ability to analyze datasets and present findings effectively.

Coursera
Skills you'll gain: R (Software), Data Import/Export, Package and Software Management, R Programming, Data Structures, Data-oriented programming, Statistical Programming, Data Analysis Software, Data Analysis, Data Science
Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: R Programming, Arithmetic, Statistical Programming, Development Environment, Programming Principles, Data Import/Export
Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Feature Engineering, Model Evaluation, Predictive Modeling, Model Deployment, Predictive Analytics, R Programming, Data Analysis, Statistical Analysis, Data Cleansing, Applied Machine Learning, Data Manipulation, Tidyverse (R Package), Classification Algorithms, Risk Modeling, Data Preprocessing, Machine Learning
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Ggplot2, Model Evaluation, Data Visualization, Regression Analysis, Predictive Analytics, Predictive Modeling, Data-Driven Decision-Making, Statistical Modeling, R Programming, Descriptive Statistics, Statistical Methods, Exploratory Data Analysis, Statistical Analysis, Data Analysis
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Descriptive Statistics, Data Analysis, Exploratory Data Analysis, Quantitative Research, R Programming, Statistical Analysis, Probability & Statistics, Statistics, Data Science
Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Web Scraping, Relational Databases, Statistical Software, Data Import/Export, R Programming, MySQL, Data Capture, Microsoft Excel
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Model Evaluation, Decision Tree Learning, Data Preprocessing, Data Manipulation, Statistical Modeling, R Programming, Supervised Learning, Machine Learning, Classification Algorithms
Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Data Manipulation, Data Transformation, Pivot Tables And Charts, Data Wrangling, Data Cleansing, Data Integration, R Programming, Data Preprocessing
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Ggplot2, Tidyverse (R Package), Data Visualization, Data Analysis, Exploratory Data Analysis, R Programming, Data Visualization Software, Data Manipulation, R (Software)
Intermediate · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Interactive Data Visualization, Software Installation, Package and Software Management, R Programming, Integrated Development Environments, Cloud Development, Cloud Hosting
Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Data Import/Export, Scripting, R Programming, Data Processing, Statistical Programming, Data Structures
Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Ggplot2, Data Cleansing, Tidyverse (R Package), Data Wrangling, Data Transformation, Data Visualization, R Programming, Data Manipulation, Data Analysis, Data Management, Pivot Tables And Charts
Intermediate · Guided Project · Less Than 2 Hours
R is a programming language and software environment primarily used for statistical computing and data analysis. It is important because it provides a robust framework for data manipulation, statistical modeling, and visualization, making it a popular choice among data scientists, statisticians, and researchers. R's extensive libraries and packages enable users to perform complex analyses and create high-quality graphics, which are essential in various fields such as finance, healthcare, and social sciences.‎
With skills in R, you can pursue various job roles, including data analyst, data scientist, statistician, and research analyst. These positions often require the ability to analyze data sets, create visualizations, and interpret statistical results. Additionally, R is valuable in industries such as finance, healthcare, and academia, where data-driven decision-making is crucial. As organizations increasingly rely on data, the demand for professionals skilled in R continues to grow.‎
To effectively learn R, you should focus on several key skills. First, understanding the basics of programming concepts is essential, including data types, control structures, and functions. Next, familiarize yourself with data manipulation and analysis using packages like dplyr and tidyr. Additionally, learning how to visualize data with ggplot2 and perform statistical analyses will enhance your capabilities. Finally, gaining experience with R Markdown for reporting and documentation can significantly improve your workflow.‎
Some of the best online courses for learning R include the Applied Data Science with R Specialization and the Data Science: Foundations using R Specialization. These courses cover essential topics such as data manipulation, visualization, and statistical analysis, providing a comprehensive foundation for anyone looking to enhance their skills in R.‎
__Yes. You can start learning r on Coursera for free in two ways:
If you want to keep learning, earn a certificate in r, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.__‎
To learn R effectively, start by exploring online courses that introduce the basics of the language. Engage with interactive coding environments and practice writing R scripts. Utilize resources like R documentation and community forums for support. Additionally, working on real-world projects can help reinforce your learning and build your portfolio.‎
R courses typically cover a range of topics, including data manipulation, statistical analysis, data visualization, and machine learning. You may also encounter specialized subjects such as time series analysis, data wrangling, and reporting with R Markdown. These topics equip learners with the skills needed to analyze and interpret data effectively.‎
For training and upskilling employees, the IBM Data Analytics with Excel and R Professional Certificate and the Data Analytics in the Public Sector with R Specialization are excellent options. These programs focus on practical applications of R in various industries, helping employees develop relevant skills that can be applied directly to their work.‎