Course: R Programming for Beginners
duration: 10 hours |
Language: English (US) |
access duration: 90 days |
Details
The free and robust statistical package R has been decades in the making and is worth learning for serious statistical operations, such as conducting new medical data analysis. This course teaches you everything you need to know to get started with R, from installing R to running R from the command line. You'll grasp how to invoke basic functions and view the documentation on those. Vectors are the easiest type of data structures in R. However, to use them successfully, it's important to appreciate their restrictions, recognize the types available, and identify their members - or components as they're officially called in R. You will learn how to create and generate vectors using the c() and vector() functions, respectively. You'll perform vectorized operations on elements in vectors. Vectors have some important limitations on the dimensions and types of data they contain. You will learn to use matrices, arrays, and lists are powerful R structures that mitigate these limitations. Finally, you will learn about Data Frames, Factors, and Strings.
Result
After completing this course you are ready to use R for statistical operations.
Prerequisites
No prerequisites.
Target audience
Business Analyst, Data analist
Content
R Programming for Beginners
R Programming for Beginners: Getting Started
- The free and robust statistical package R has been decades in the making and is worth learning for serious statistical operations, such as conducting new medical data analysis.
- This course teaches you everything you need to know to get started with R, from installing R to running R from the command line.
- You'll grasp how to invoke basic functions and view the documentation on those. You'll create variables in R and explore various reserved words and the = and <- operators.
- You'll then perform basic arithmetic operations on variables, invoke built-in functions, and work with various atomic data types, such as character, integer, double, logical, complex, real, and raw.
- By the end of this course, you'll have the skills you need to get working with R.
R Programming for Beginners: Exploring R Vectors
- Vectors are the easiest type of data structures in R. However, to use them successfully, it's important to appreciate their restrictions, recognize the types available, and identify their members - or components as they're officially called in R.
- This course shows you how to create and generate vectors using the c() and vector() functions, respectively.
- You'll perform vectorized operations on elements in vectors. Practice filtering and slicing vectors. And use the which(), any(), and all() functions on vectors.
- Furthermore, you'll perform naming and indexing operations on vectors and work with different length vectors using vector recycling.
- On completing this course, you'll have the knowledge and know-how to utilize vectors for their intended purpose.
R Programming for Beginners: Leveraging R with Matrices, Arrays, & Lists
- Vectors are a great basic data structure in R, but they have important limitations on the dimensions and types of data they contain. Matrices, arrays, and lists are powerful R structures that mitigate these limitations. This course will help you distinguish each of these three elements' purpose and show you how to use them.
- You'll start by using matrices to store two-dimensional data. You'll then differentiate between row-major and column-major matrices.
- You'll learn how to use arrays and how you can easily create three-dimensional arrays as you can two-dimensional arrays.
- You'll then move on to the use of lists and how they differ from vectors. After taking this course, you'll be able to identify when and how to use a matrix, a list, and an array.
R Programming for Beginners: Understanding Data Frames, Factors, & Strings
- Data frames are an R abstraction for tabular data similar to that contained in spreadsheet files or database tables. Data frames can work directly with files in the CSV, JSON, and Excel format, all common formats used to store data.
- This course outlines the characteristics of data frames in the R programming language and demonstrates how to use them.
- You'll learn to create basic R data frames from multiple vectors. You'll use factors - similar to enums or enumerated types in other programming languages and great for categorical variables.
- You'll also learn how to perform various string manipulation operations, such as splitting and joining strings and changing case. You'll then practice the important topic of printing precisely formatted strings with placeholders for variable values.
- When you're done, you'll be able to use data frames, factors, and strings professionally in your R programming projects.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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