Free Online Data Analysis Course - R programming | Alison

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R for Data Analysis

Learn about the R language for data analysis and statistical computing with the help of this free online course.

Data Science
Free Course
This free online R for Data Analysis course will get you started with the R computer programming language. In this course, you will learn how the data analysis tool, the R programming language, was developed in the early 90s by Ross Ihaka and Robert Gentleman at the University of Auckland, and has been improving ever since. You will also learn about how data analysis systematically evaluates data using analytical and logical reasoning, and more!





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This course will first cover the topic of manipulating and grouping data so that can you prepare and organize your output. You will then learn how to present this output via visualizations. You will also study important packages such as dplyr, tidyr, readr, data.table, SparkR, and ggplot2, along with how these packages can make data manipulation, visualization, and computation much faster. The course will then show you the crucial difference between a feature manipulation and observation manipulation.

Next, you will study the main two types of data visualization. Data visualization is a term that describes any effort to help people understand the significance of data by placing it in a visual context. It exposes patterns, trends, and correlations that might go undetected in text-based data, and makes these patterns more easily recognizable. Finally, you will learn about the grammar of graphics, the different graphing and charting libraries needed for your visualizations, how to set of colours, and how to organize data in your visualizations.

This R for Data Analysis course will be of great interest to professionals working in the areas of data science and data analysis. It would also be valuable to learners who want to get started with R for statistical computing. By the end of the course, you will have a valuable data analysis tool in your belt, which will make your statistical résumé, and output, much stronger. So why wait? Get started with this course today, and learn a valuable new skill in no time.

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Learning Outcomes

On completing this course, you will be able to: - List libraries/packages you will need to include in your program for data manipulation. - Discuss the process of features and observation manipulation. - Describe how the forward pipe operator helps cleans up and organize your code. - Explain what data visualization is and the difference between its two types. - List libraries you will need to include in your r program to create visualizations. - Describe how to display your data on a visualization.


All Alison courses are free to enrol, study and complete. To successfully complete this Certificate course and become an Alison Graduate, you need to achieve 80% or higher in each course assessment. Once you have completed this Certificate course, you have the option to acquire an official Certificate, which is a great way to share your achievement with the world. Your Alison Certificate is:

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