R Fundamentals (125523845) - Online

Description

CPA Members only

CPA Australia has partnered with the Corporate Finance Institute (CFI) to curate a collection of data and digital courses exclusively for CPA members. CFI courses have an emphasis on hands-on, practical learning and skills acquisition. They teach in-demand industry practices, tools and techniques that help accounting and finance professionals build confidence, stand out from the competition, and make a positive impact on their careers.

Start your hands-on data science journey by coding in R programming language. In this course, you’ll progress from coding with Base R to creating a full data science project with Tidyverse packages in RStudio. You’ll begin this course by exploring the foundations of Base R to generate outputs, create variables, and conduct statistical analysis. We’ll then expand on the functionality of analysis by importing Tidyverse packages and structuring our project in RStudio IDE. As we progress, you’ll learn to import, clean, transform, and visualize data for your project, following the data science process taught in our BIDA program.

This CFI course involves specific technical requirements, so we encourage you to review them here.

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Our Privacy Policy includes the following statement under the subsection 'Links to external websites':  
•    We may provide links to websites operated by third parties. 
•    We are not responsible for the privacy practices or the content of such websites which will be governed by their own privacy policies to which you are advised to refer. 
•    Your satisfactory completion of the course may be recorded in your CPD Diary.

CFI programs will be supplied to CPA Australia members as standalone courses for 12 months from the date of purchase and as such, any associated CFI certifications are not able to be supplied. Refunds or extensions for purchases of CFI courses will only be available in exceptional circumstances and will be based on CPA Australia and CFI’s cancellation terms.

Learning objectives

• Write R code to generate outputs, create variables, and conduct statistical analysis
• Apply best practices to manage our coding workflow
• Structure data sets, scripts, and outputs to create a shareable project in RStudio
• Import and clean our data using Tidyverse packages (e.g., readr and tidyr)
• Transform and visualize our data using Tidyverse packages (e.g., dplyr and ggplot2)

Audience