In this course, you’ll learn the fundamental tools and packages to manipulate, organise, analyse, and visualise data using the R programming language in the RStudio developer environment.
This course is for those who are interested in learning the R programming language for the purposes of data manipulation, statistical computing, and graphical display of data.
The course includes a series of video lectures combined with a variety of conceptual and hands-on activities to help you develop skills in manipulating and analysing data, interpreting results, and visualising your data effectively.
R is widely recognised as a powerful programming language and environment for data manipulation, statistical computing, and graphical display. R provides a variety of tools and techniques and is easily extensible. It’s an open-source programming language and a vital tool for data wrangling and analysis. R also includes a robust data handling and storage facility, as well as an extensive, integrated collection of tools for data analysis and graphical display.
You’ll explore all of this and more as you work through the three modules of the course and test your understanding with the knowledge tests at the end of each section.
Module 1: R Programming for Beginners
Getting Started with R; Exploring R Vectors; Leveraging R with Matrices, Arrays, and Lists; Understanding Data Frames, Factors, and Strings
Module 2: Datasets in R
Loading and Saving Data; Transforming Data; Selecting, Filtering, Ordering, and Grouping Data; Joining and Visualising Data
Module 3: Statistical Analysis and Modelling in R
Working with Probability Distributions; Understanding and Interpreting Statistical Tests; Statistical Analysis on Your Data; Performing Regression Analysis
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The aim of the course is for you to develop a strong foundation in the R programming language that you can put to effective use in the field of data analysis.
Strong critical-thinking and problem-solving skills, a strong background in mathematics (e.g., advanced algebra), and some experience with coding.
Wherever possible our training is tailored to your needs. The cost of our training programmes depend on the course(s) you choose and varies according to duration and breadth. Rest assured we have a number of payment options available to ensure the cost of training is affordable and can be worked alongside your other financial commitments. Common ways people fund their training include: –
Requesting funding from your employers needn’t be a daunting task. Many employers support and encourage their employees with their professional development and consider it a worthwhile investment to fund any training required.
What we can help with:
* Terms and Conditions apply. Speak to a Course Advisor for full information on the options available to you.
To become an effective data analyst, you’ll need several programming languages in your toolkit. R is among the most sought-after skills among data analysts.
We offer a range of training packages in a range of subject areas and can offer blended learning opportunities to best meet your needs.
Our courses are practical in nature and focus on a single subject and can last anywhere from a few hours to a few days.
Diplomas are designed to give you a complete skillset mapped to a specific career path and contain a number of core and elective courses.
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