Introduction to R for Data Science
Gain a better understanding of the installation and the uses of the R programming language for data science.
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This course begins by teaching you how to install Microsoft R Open on your computer. R is a programming language and software environment for statistical computing. With this course, you will learn that it was initially started as a research project before becoming a programming language and the most popular language for Data Science. You will also study the 5 basic data types as well as the data structures in R programming which include the vector, list, matrix, data frame, and array.
You will then look into how helpful Enzo Unified is for Data acquisition and study the applications and services it can connect to. Enzo Unified is a service platform that transparently makes data access easier. With this course, you will learn that it can abstract protocols, unify data formats, remove semantic differences, and simplify and augment authentication. You will also look into the abstracted APIs or adaptors that you can use or add to, and more!
If you already have some knowledge of programming languages and an understanding of using SQL Server management studio, learning more about using R for statistical computing will greatly enhance your programming skills. Upon the completion of this course, you will be able to install Microsoft R Open on your own computer, use the different data types in R programming, and much more! Sign up for this course and learn how to set up and use the R language.
Module 1: Introduction to R
Module 2: Enzo Unified and Data Aggregation
Module 3: Introduction to R for Data Science Assessment
On completing this course you will be able to: - Explain how to install Microsoft R Open on your own computer. - Recognize the different data types in R programming. - Identify how the different data Structures work in R programming. - Identify how helpful Enzo Unified is for Data acquisition. - Recognize the applications and services that Enzo Unified can connect to.
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