Name: R Introduction: Part I
Rating: 4.5 (2 reviews)

R Introduction: Part I

R is one of the most popular programming languages among data analysts and data scientists. R has a wide community that will always help you with any problem. Also, R has tons of different packages designed to solve various problems. The language can be easily applied to statistics and data analytics problems. In the first part, you will be introduced to the very basics of R and will deal with single 1-D values of different types.

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Gain insight into a topic and learn the fundamentals

4.5

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Beginner

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26 chapters

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Learning outcomes

Modules

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Outcomes

Learning outcomes

Modules

Testimonials

Recommendations

Codefinity advantages

FAQs

What you will learn

Grasp basic R syntax and operations to manage data effectively.
Become proficient with vectors, mastering their creation, naming, and indexing for data manipulation.
Understand factors for categorical data handling, including indexing and summarizing.
Apply operations on vectors and factors to summarize grades and intervals.

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Assessments25 assignments

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There are 6 modules in this course

In the initial section, you’ll dive into the foundational elements of R, such as generating output and performing elementary operations. This section will conclude with an exploration of the theory behind variables.

You’ll become familiar with the vector class in R, which also handles individual values. Here, you’ll delve into the primary data types for singular values and learn how to manage multiple values of the same type simultaneously.

Factors, also known as categorical variables, are prevalent in the real world. Examples include blood types, currencies, nationalities, and brands. Unlike numerical variables, factors have a limited set of possible values.

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Showing 2 of 2 reviews

Reviewed on Aug 26, 2024

The platform is friendly.

Reviewed on Jul 10, 2024

The lessons are very straightforward and presented in a way to build a solid foundation of knowledge. As with any lesson, more examples and more practice is always welcome.

Recommended if you're interested in learning R

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