In the dynamic landscape of data science and statistical analysis, there has been one constant in a programming language that has stood the test of time. This language has been a trusted companion for researchers, analysts, and data enthusiasts alike, R. R is a popular open-source programming language and software environment specifically designed for statistical computing and data analysis. It provides a wide range of libraries for data visualization which makes it a powerful tool for creating various types of data visualizations, like charts, graphs, and plots.
Some commonly used packages for data visualization in R include ggplot2, lattice, and base R graphics. If you are interested in working in data sciences Data Analysts, Statisticians, and Data scientists, then looking into one of these courses could best be for you.
Within the content of this article, we will take a look at the best R courses available, that will teach you all the skills you need to know to become experienced in R programming. All 5 courses each contain the key information you’ll need to know on R programming, with certificates that are even sharable on LinkedIn.
For some more information related to R see the following: 6 Reasons to Learn R for Data Science and Programming Languages. Which one to choose?
Table of Contents
- Getting Started with Data Visualization in R
- Practical Time Series Analysis
- Data Analysis with R Programming
- Data Visualization & Dashboarding with R Specialization
- Advanced-Data Visualization with R
- Conclusion
Getting Started with Data Visualization in R
This course will provide a solid foundation to begin learning how to build your subject matter expertise to process data for visualizations, and set up R**.** Your instructor for this course is Collin Paschall a senior lecturer and program coordinator with the Center for Advanced Governmental Studies at Johns Hopkins University.
The duration of this course lasts for 9 hours to complete at just a beginner level, requiring no previous experience.
During this course, you will:
- Learn new concepts from industry experts.
- Become familiar with the basics of this tool.
- Develop job-relevant skills with hands-on projects.
- Earn a shareable career certificate.
Using data visualization is a crucial skill for anyone who will actively be using quantitative data, which is why knowing how to use R statistical programming language is critical. The course has 3 modules consisting of 3 quizzes and 6 assessments before completion, each module targeting a different aspect of R for beginners to get a real introduction to using the tool.
Practical Time Series Analysis
Practical time series analysis is the application of time series analysis techniques using the R programming language. These are incorporated to solve real-world problems or gain insights from time-ordered data, Time series analysis is a crucial component of data science and statistics that deals with data points collected at regular time intervals.
This course will educate users who have some technical competencies and would like more than a step-by-step approach. The course is taught by 2 instructors Tural Sadigov and William Thistleton. The duration of this course lasts for 24 total hours to complete or 8 hours a week for 3 weeks. The course is offered to students at an intermediate level with a flexible schedule allowing the students to learn the material at their own pace.
You will take a look at:
- Several mathematical models explain the processes that generate these types of data.
- Also looking at graphical representations that provide insights into the data that is provided.
- As well as learning how to make forecasts that say intelligent things about what you can expect in the future.
The course has modules, each covering a different aspect of practical time series analysis. Ranging from basic statistics working your way up to more complex branches of knowledge like seasonality, SARIMA, and forecasting. There are 19 assessments along the way that a student will work on before completion.
Data Analysis with R Programming
This course will equip you with the skills needed to apply to introductory-level data analyst jobs. In this course, you’ll learn about R programming language. You will be taught the interworking of RStudio and how to use it. This course will also go through the software’s functionality, potential applications, and unique R-specific features, which include R packages.
Your instructor will be Google Career Certificates (a top instructor), who are a part of Grow with Google, which serves to help people and businesses grow. The course experience is recommended for a beginner level, with flexible scheduling and a total of 36 hours for completion.
What students are expected to learn is:
- Have the ability to describe the R programming language and its programming environment.
- Be able to explain the fundamental concepts involved with programming in R including functions, variables, data types, pipes, and vectors.
- List the possibilities for creating visualizations in R.
- Will show that you are familiar with R Markdown’s fundamental formatting in order to give your material shape and emphasis.
- Work with contents and components of R packages including the Tidyverse package.
- Earn a shareable career certificate from Google.
The course includes 5 modules, starting with the 1st programming and data analytics. The 2nd module is programming using RStudio, 3rd working with data in R, 4th more about visualizations, aesthetics, and annotations. With the final module being documentation and reports.
Data Visualization & Dashboarding with R Specialization
This is a 5-course specialization that is meant for students seeking to develop the ability to visualize data using R. Through five courses, you are going to use R to create static/interactive data visualizations and publish them on the internet. This is going to prepare you to provide insight to all sorts of different audiences. This course experience level is considered for beginners, learning at your own pace, for a length of 2 months at 10 hours a week. Your instructor will be Collin Paschall, who as mentioned earlier is a program coordinator with the Center for Advanced Governmental Studies at Johns Hopkins University.
Increase your expertise in:
- Learn from academic and industry pros about in-demand skills.
- Master a subject with hands-on projects.
- Develop a deep understanding of key concepts.
The 5 courses included are Getting Started with Data Visualization in R, Data Visualization in R with ggplot2, Advanced Data Visualization with R, Publishing Visualizations in R with Shiny and Flex Dashboard, Data Visualization Capstone.
All in all, this 5-course specialization provides an incredible opportunity for anyone interested in learning how to use R programming and data visualization. This specialization is well-constructed, with an instructor who is well-educated with a great understanding of the subject matter.
Advanced-Data Visualization with R
Advanced Data Visualization with R involves the use of the R programming language to create complex, informative, and visually appealing data visualizations that go beyond basic charts/graphs. Advanced data visualization techniques in R include leveraging the specialized libraries, and creative approaches to try to convey insights from complex datasets.
This course is the third specialization in Data Visualization and Dashboarding in R. Students come into this course with a foundation using R to make many basic kinds of visualization, usually with the ggplot2 package. This course’s main focus is on expanding the student’s inventory of data visualization options.
With a length of 8 hours and a flexible schedule, this course is very accommodating for completion. Your instructor will be a familiar face we’ve seen in a lot of these courses Collin Paschall.
During this course, you will:
- Draw on additional packages to supplement ggplot2.
- make more variants of traditional figures, as well as venture into spatial data.
By the end of this course, students can:
- Data utilize import capability
- Utilize tools from the well-known tidyverse package to modify that data.
- Make simple reports using R Markdown.
There are only three modules in this course, module 1 is “Advanced figures with ggplot2”. Module 2’s topic is “Spatial Data” and module 3 is “Plotty and ggnimate”. Along with the modules, there are six quizzes to be done before certification.
Conclusion
All in all, the world of data science and statistical analysis continues to rely on R as a loyal companion. This selection of top R courses provides a valuable opportunity for individuals seeking to harness the power of this open-source programming language. Whether you aim to master data visualization, delve into time series analysis, embark on a data analyst career, or specialize in advanced data visualization, these courses offer the best path to enhance your R programming skills. With certificates shareable on platforms like LinkedIn or you can add them to your resume/CV, these courses not only equip you with knowledge but also open doors to new career heights.
