What are the best online courses for learning R? (2024)

How to Master R and Become a Data Wizard! 🧙♂️I'd recommend:- Coursera's R Programming for stats and data analysis fundamentals. 📊- CareerFoundry’s free course for a quick, engaging R introduction. 🚀- Harvard’s EdX courses for a deep dive into data science with R. 🏫- LinkedIn Learning's Data Analyst track to start from scratch in R. 👩💻- Coursera’s Google Data Analytics Certificate for a comprehensive R skillset. 📈- Practice regularly – the best way to learn R is by doing. 💪- Join online forums and communities for help and networking. 🌐

For mastering R basics, consider "Introduction to R" on DataCamp. Its hands-on exercises provide a practical grasp of fundamental concepts. "R Programming" on Coursera by Johns Hopkins University is another gem, blending theory with real-world application. These courses offer a solid foundation for diving into the world of R programming.

For mastering R in the realm of data science, consider enrolling in "Data Science: R Basics" on edX by HarvardX. This course, the initial part of a comprehensive nine-course series, introduces essential tools and techniques for data exploration, cleaning, transformation, and modeling with R. Delving into data frames, vectors, matrices, and lists, the curriculum covers basic functions and packages. Notably, the course is self-paced and free, making it accessible for learners at their convenience. With over 1,000 ratings and a 4.5-star rating, it stands as a highly regarded resource for those aspiring to build a strong foundation in utilizing R for data science.

I can recommend the LinkedIn Learning path "R for Data Science" that gives you great hands-on insights. Make sure to have the "R Essential Training" done before that if you haven't had to many overlays with R. Both courses require a basic understanding of statistical logics.

Embark on the captivating field of machine learning with the "Machine Learning with R" course provided by DataCamp. Tailored for those eager to harness R for machine learning, the course instructs on the practical application of various algorithms and methods to real-world challenges. Exploring classification, regression, clustering, dimensionality reduction, and ensemble methods, the curriculum utilizes the caret package and other libraries. Notably, the course is hands-on and interactive, fostering a dynamic learning experience. Boasting over 20,000 ratings and a stellar 4.7-star rating, it stands as a highly recommended resource for individuals seeking to delve into the world of machine learning using the R programming language.

Dive into the exciting realm of machine learning with "Machine Learning with R" by DataCamp. This course is your gateway to applying R in real-world problem-solving, covering key topics like classification, regression, clustering, and more. Utilizing the caret package and other libraries, it offers an interactive, hands-on experience. With over 20,000 ratings and an impressive 4.7-star rating, it's a stellar choice to master machine learning with R. Happy exploring!

Developing effective data visualization skills is crucial for data analysts to communicate insights. To create compelling graphs and charts using R, consider enrolling in the Coursera course "Data Visualization in R with ggplot2." This program guides you through utilizing the powerful ggplot2 package and other tools to craft informative visualizations, covering a range of plot types including scatterplots, histograms, bar charts, and boxplots. The course emphasizes customization and enhancement techniques. As part of a specialization, it has garnered over 2,000 ratings, boasting a commendable 4.6-star rating. Elevate your proficiency in R and enhance your ability to convey data-driven insights through visually impactful presentations.

1. Data Visualization and Reporting in R (LinkedIn Learning):This LinkedIn Learning course covers data visualization techniques in R, including creating charts and graphs for effective reporting.2. Interactive Data Visualization with R, plotly, and shiny (Coursera - Duke University):Offered by Duke University on Coursera, this course explores interactive data visualization using R, plotly, and shiny. It's part of the "Mastering Software Development in R" specialization.

The "Statistics with R" course offered by Duke University on Coursera sounds like a solid choice for anyone looking to build a strong foundation in statistics using R. Duke University is known for its reputable programs, and this course appears to cover a comprehensive range of statistical topics.

Establish a strong foundation in data analysis by mastering statistical tests and calculations with R. The "Statistics with R" course, provided by Duke University on Coursera, is a valuable resource for understanding statistical concepts and their implementation using R. Covering topics like probability, inference, regression, ANOVA, and Bayesian analysis, the course utilizes base R functions and additional packages. Forming part of a specialization, it has earned acclaim with over 3,000 ratings and an impressive 4.7-star rating. Delve into the world of statistics with R to enhance your analytical skills and gain practical insights into applying statistical methods to diverse data sets.

Unlock the potential of text data through text mining, the process of extracting valuable information from documents, tweets, reviews, and articles. To harness the power of R for text mining, consider enrolling in the Coursera course "Text Mining and Analytics" by the University of Illinois at Urbana-Champaign. This comprehensive program guides you through working with text data, covering preprocessing, tokenization, sentiment analysis, topic modeling, and word embeddings. Utilizing the tm package and other tools, the course explores text similarity, classification, clustering, summarization, and visualization.

Dive into the realm of text mining with "Text Mining and Analytics" by the University of Illinois at Urbana-Champaign on Coursera. This course equips you with essential skills in preprocessing, tokenization, sentiment analysis, topic modeling, and word embeddings. Explore text similarity, classification, clustering, summarization, and visualization using the tm package and other tools. As part of a specialization, it boasts over 1,000 ratings and an impressive 4.5-star score. Unleash the power of R to derive valuable insights from textual data. Happy exploring!

Along with the ones listed above I would say that DataCamp also has a nice track to learn R. The key with Data Camp is to practice with the guided code and then erase it all and try it yourself.

Start with the free information presented by Hadley Wickham (A godfather of the R programming language). Google the search term "Hadley Wickham R," and then look for the text R for Data Science. That is an excellent introduction to the R programming language for Data Science. If you want a comprehensive (Paid) resource to learn, refine, and deepen your understanding of the R programming language, Google "Business Science R." The page "Learn Data Science for Business" has a five-course R program with over 150 hours of video content, dozens of small projects, and the ability to interact with the instructor (Matt Dancho) for an indefinite period (You have access to the course material for life).