.png){kind=logo}
In respect to a data scientist and statistician or an analyst for that case, the learning of the R programming language can never be overemphasized. R programming is a language built for statistical computing, data analysis, and graphical viewing. A useful unit in career building, concerning the demand increase among professionals involved in data-driven decision-making, is learning R. Let us therefore try to explore some of the best online courses through which one can learn R programming and take a closer look at what each has to offer.
R Programming by Johns Hopkins University is a beginner course for the data science specialization available through Coursera. The course is oriented towards introducing the learner to the basic concepts of R programming. If you want to master R programming, then this is the right course for you.
Instructor: Roger D. Peng, PhD, Associate Professor, Department of Biostatistics
Duration: ~57 hours
Level: Beginner to Intermediate
Certification: Yes, upon completion.
Content: Basics of R, data types, subsetting, vectorization, and control structures. Includes also an introduction to debugging and profiling of R code.
Format: Video lectures, readings, quizzes, peer-graded assignments.
Created by a top-ranked university with experienced instructors. It's part of a more significant specialization that enables research in any topic in the data science domain to full depth.
The best skills can be updated after doing this course of Introduction to R for Data Science by Microsoft. The topics should include data types, vectors, matrices, conditional statements, loops, functions, and visualization.
This is what prepares beginners to write programs using R in the framework of a new knowledge area: data science.
Instructor: Graeme Malcolm, Senior Content Developer with Microsoft
Duration: 4 weeks, 2-4 hours/week
Level: Beginner
Certification: Yes, though payable
Content: Data types that include vectors, arrays, lists, and data frames. Importing of data and basic data manipulation and visualization in R
Format: Theoretical lessons, practical labs and courses, quizzes
Done by the best companies in the tech industry, hence with first-hand information about the presence of data manipulation techniques in the real world and their applications. Largely concerned with the practical application of visualization and the techniques of data manipulation.
This is an exhaustive course by DataCamp and, according to the learning platform's terminology, the R Programming Track. It's going to aid one in acquiring the basic and professional knowledge necessary to ensure effective use of the R programming environment. Several courses shall be captured within this track; each gives a different view of the usage of R programming.
Course Instructor: Multiple instructors, all experienced in their subjects.
Duration: Self-paced, but it will be approximately around 60 hours if one wants to finish all the expectations of the track.
Level: Beginner to advanced.
Certification: There is a separate certification for every course.
Content: The basic syntax in R and data structures, data manipulation with dplyr, techniques for data visualization with ggplot2, ways to perform statistical modeling, and introduction to machine learning.
Format: Interactive coding exercises, video tutorials, projects at the end.
Quite interactive with immediate feedback on coding exercises. This is a course with deep coverage of aspects of R programming and data science in general.
The Udacity Programming for Data with R Nanodegree, as it implies, aims to empower students with a foundational understanding of data analysis alongside R programming.
Instructors: More in number and all are industry-experienced
Duration: Approximately 3 months, 10 hours/week
Level: for all levels of learners
Certification: Nanodegree
Content: It covers R programming basics, data wrangling, data visualization, Data Science with SQL, and version control with Git and GitHub.
Format: Video and practice exercises.
It has video lectures, quizzes, projects, and mentor help. It provides benefits like project-based learning practice. Mentorship and career services are also provided, covering everything from resume-building help to job assistance.
Learn how to use the tools natively provided in R to visualize data and how to create custom visualizations in R with LinkedIn Learning’s R for Data Science: Analysis and Visualization
Instructors: Barton Poulson: Instructor, Professor of Psychology, Founder datalab.cc
Duration: 6 hours of content
Level: Beginner to Intermediate
Certification: Certification available upon completion
Content: Basic R syntax, data structures, data visualization; how to conduct statistical analysis and reporting
Format: Video and practice exercises.
Information that is learned quickly, relevant, and non-overwhelming. You can connect your LinkedIn profile to the share certificate.
Learn R by Codecademy is an elementary interactive training plan for beginners. The platform will help its learners become programmers in R with the help of real-world exercises.
Instructors: Interactive platform with inbuild code editor
Time: About 20 hours
Level: Introductory
Certificate: Pro membership available
Content: Basic syntax, data frames, data manipulation, data visualization.
Format: Interactive, including quizzes and projects.
Interactive learning with real-time results. Engaging learning experience with rewards and tracking completion.
Data Science: R Basics is a Harvard University-edX initiative. In this, the students will be taught about the basics of programming in R and data analytics as one part of its more generic program, Data Science Professional Certificate.
Instructor: Rafael Irizarry, Professor of Biostatistics
Length: 8 weeks, 2-4 hours per week
Level: Beginner
Certificate: Those who seek certification shall pay for it
Course content: R basics, data visualization, and introductory data analysis techniques
Course format: The course is a mix of Video Lectures, Exercises, and projects
Created by a world-famous university. Comes as part of the entire data science certification course.
Yet another course sitting within Udemy is run by Jose Portilla, and Data Science and Machine Learning Bootcamp is the boot camp that has given all-around knowledge of data science and machine learning using R. Although this platform has amazing courses for R programming, Coursera remains Udemy’s top competitor.
Instructor: Jose Portilla, Head of Data Science at Pierian Data Inc.
Level: From beginner to intermediate
Duration: 17 hours of video content
Certification: upon completion
Course content: R programming, data visualization, machine learning algorithms, practical projects in data science
Course format: Video lectures, quizzes, hands-on projects
This would be a fully comprehensive course on data science and machine learning. Since there would be hands-on projects incorporated in between, using datasets to solve real-life problems will give you a feel of what it is like to work as a Data Scientist. This is a hands-on, practical course in R data science powered by FutureLearn and done in association with the partnership of top universities.
It can, therefore be concluded that regardless of whether someone is interested in the field of data science or statistics or even data analysis and then programming, one would consider it a valuable investment as per the above reasons. The best options regarding these can be found above, through varieties of courses that are pocket-friendly, and consideration is given to the different learning styles and schedules. The above-mentioned basic courses will provide you with a roadmap to R programming. From interactive exercises to project-based learning and boot camps, you will find your ideal course that will help extract R programming for better career prospects.
