Every year, the number of R users grows by 40% and an increasing number of organizations are using it in their day-to-day activities. And there are tons of resources available to learn R for Data Science.
Since there are seemingly thousands of courses, books, tutorials, and white-papers written about R for Data Science, we chose to consider the best and highest-rated courses in this article.
You can Leverage the power of R by completing any of the notable courses highlighted below. These courses are professionally produced, the sound quality is excellent, and the explanations are concise and clear.
5+ Best Courses to Learn R for Data Science in 2019
We have reviewed the content and community support for these courses. They bring an incredible value for your financial and time investment as most of them come with an immediate and personalized feedback on every exercise.
1. Introduction to RÂ [đHighly Recommended]
Plus, you will find out how to perform data analysis using R and learn all the important techniques to create and use; vectors, matrices, factors, data frames and lists.
Is it right for you?
This Course is suitable for beginners with no coding experience or formal background in R. There are no pre-requisites for this course.
In this Course, you will get a really nice walk through of the concepts with coding examples in R with very helpful talks in between sections that provide a clear overview of each topic.
What you will learn?
- The first steps with R and the basic data types in R.
- Creating vectors in R, name them, select elements from them and compare different vectors.
- Importance of factors in data analysis, create, subset and compare them.
- Create matrices and understand the basic computations.
- In-depth introduction to Data Frames.
- Create, name and subset lists.
Learning Path: Data Scientist with R
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2.Data Science Specialization[đHigh Value]
Data Science Specialization is a nine-course introduction to data science, created by John Hopkins University and taught by leading professors. You will learn how to get your data into R, clean and transform data into the most useful structure.
You also will gain functional knowledge of statistical concepts, reproducible research for scientific claims, and Machine Learning.
Is it right for you?
This Specialization is suitable for beginners with no coding experience or formal background in statistics. This specialization will equip you with key concepts and tools you’ll need throughout the entire data science pipeline.
What you will learn?
- The Data Scientists Toolbox
- R Programming
- Getting and Cleaning Data
- Exploratory Data Analysis
- Reproducible Research
- Statistical Inference
- Regression Models
- Practical Machine Learning
- Developing Data Products
- Data Science Capstone
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3. Introduction to Data Science
Build a strong foundation in R and start exploring data-related careers in this introductory course. The 100-hour curriculum was curated by experts who analyzed skills required in entry-level data science jobs. It includes more than 40 hours of project work.
While youâll learn the fundamentals of data scienceâincluding data wrangling, probability and statistics, exploratory data analysis, and moreâyouâll also complete a capstone project, giving you the chance to work in a realistic data science scenario.
Is it right for you?
Some background in programming (basic familiarity with variables, functions, loops; experience with any language) is helpful, but beginners are welcome! There are no pre-requisites for this course.
To set you up for success, this self-paced course includes one-on-one mentorship from a working data scientist and support from student advisors, plus access to a global community of fellow learners and alumni.
What you will learn?
- Programming in R
- Data wrangling
- Probability and statistics
- Exploratory data analysis
- Data storytelling
- Data visualization
- Preparing for data science job interviews
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4. Data Science with R
This course is created by Matthew Ranze who is a Data Science Consultant, Author and has 17 years of professional experience working with tech startups to Fortune 500 companies.
The topics covered in this course will help you to understand the practice of data science, R programming language, and how to create Data Visualization and Statistical models.
Is it right for you?
This course is right for you if youâre interested in learning R for Data Science and you donât need any background in analytics or programming to get started.
By the end of this course, you’ll have an understanding of the principles of data science to transform your data into actionable insight.
What you will learn?
- Introduction to R and its use for Data Science.
- Working with Data
- Creating Descriptive Statistics
- Creating Data Visualizations
- Creating Statistical Models
- Handling Big Data
- Predicting with Machine Learning
- Deploying Data to Production
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5.Statistics with R Specialization[ đ High Value]
Statistics with R Specialization is offered by Duke University on Coursera and will help you to master statistics with R.
You will learn key statistical concepts and techniques for performing exploratory data analysis in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of correlation, regression and statistical inference.
Is it right for you?
What you will learn?
- Introduction to Probability and Data
- Inferential Statistics
- Linear Regression and Modelling
- Bayesian Statistics
- Statistics with R Capstone
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6. Data Science Certification Training – R Programming
The Data Science Certification with R offered by Simplilearn is suitable for beginners. This training program forms an ideal package for all the Data Science novice’ aspiring to build a successful career in Data Analytics or Data Science.
By the end of this training, learn the art and techniques required for data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R programming.
Is it right for you?
What you will learn?
- Gain a foundational understanding of business analytics
- Install R, R-studio, and workspace setup, and learn about the various R packages
- Master R programming and understand how various statements are executed in R
- Gain an in-depth understanding of data structure used in R and learn to import/export data in R
- Define, understand and use the various apply functions and DPYR functions
- Understand and use the various graphics in R for data visualization
- Gain a basic understanding of various statistical concepts
- Understand and use hypothesis testing method to drive business decisions
- Understand and use linear, non-linear regression models, and classification techniques for data analysis
- Learn and use the various association rules and Apriori algorithm
- Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering
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Thanks for making it to the end :~)
If you liked this article, I’ve got a practical reads for you one about the Best Data Science Courses and one about Data Science BootCamp with a Job Guarantee.
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