About This Course
To be a well-rounded data scientist, it is imperative to know the ins and outs of both Python and R, the latter of which we will discuss in this course. In addition to all the primary coding functionality, we will learn more about what makes R unique, diving into how R leverages vectors and matrices to read in and work with data.
Additionally, we will discuss the mechanics of the powerful dplyr library, which allows extreme ease in manipulating datasets. We will then discuss data visualization, highlighting the advantages of the highly customizable ggplot2 library, which powers some of the most intricate graphs seen in data journalism and research today.
Finally, we will go through basic statistics and discuss the statistical tools within R, such as constructing confidence intervals, hypothesis testing, and ANOVA testing.
We will cover the following topics:
- R fundamentals
- Working with data: Dplyr
- Data visualisation in R
Who is this course suitable for?
Anyone who is looking to understand more about R Programming with a view to break into a career in either software development, Data Analysis or Data Science. Equally, you may be a professional working in tech or finance and want to learn new analytical techniques that can enhance your overall skillset.
Our Promise to You
By the end of this course, you will have learned R programming.
30 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.
Get started today and learn more about the fundamentals of R programming.
|Section 1 - R Fundamentals|
|RStudio And RMarkdown||00:00:00|
|R vs. Python, Basic Math, Boolean||00:00:00|
|Some Useful Vector-Based Functions||00:00:00|
|Strings And Characters||00:00:00|
|For Loops And While Loops||00:00:00|
|Section 2 - Working With Data:Dplyr|
|Intro To Working With Data||00:00:00|
|Group By And Summarise||00:00:00|
|Section 3 - Data Visualization In R|
|Basic Plots In R||00:00:00|
|Intro To ggplot2 And Creating Scatterplots||00:00:00|
|Section 4 - Statistics|
|One Sample T-Test||00:00:00|
|Two Sample T-Test||00:00:00|
|Two Sample T-Test Of Proportions||00:00:00|