This course is designed for those interested to learn the basics of R programming together with data visualisation, the mechanics of a powerful dpylr library, and statistics.
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Who this course is 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.Â
- Equally, you may be a professional working in tech or finance and want to learn new analytical techniques that can enhance your overall skillset.
What you’ll learn:Â
- R fundamentals
- Working with data: dplyr
- Data visualisation in R
- Statistics
Requirements:Â
- No prior knowledge is required to take 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.Â
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.
Our Promise to You
By the end of this course, you will have learned R programming.
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Course Curriculum
| Section 1 - R Fundamentals | |||
| RStudio And RMarkdown | 00:00:00 | ||
| R vs. Python, Basic Math, Boolean | 00:00:00 | ||
| Variable Assignment | 00:00:00 | ||
| Vectors | 00:00:00 | ||
| Matrices | 00:00:00 | ||
| Some Useful Vector-Based Functions | 00:00:00 | ||
| Strings And Characters | 00:00:00 | ||
| Conditionals | 00:00:00 | ||
| For Loops And While Loops | 00:00:00 | ||
| Defining Functions | 00:00:00 | ||
| Shiny Dashboards | 00:00:00 | ||
| Section 2 - Working With Data:Dplyr | |||
| Intro To Working With Data | 00:00:00 | ||
| Select | 00:00:00 | ||
| Filter | 00:00:00 | ||
| Mutate | 00:00:00 | ||
| Arrange | 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 | ||
| Boxplots | 00:00:00 | ||
| Barplots | 00:00:00 | ||
| Histograms | 00:00:00 | ||
| Faceted Graph | 00:00:00 | ||
| Section 4 - Statistics | |||
| Correlation Coefficients | 00:00:00 | ||
| Standard Deviations | 00:00:00 | ||
| Confidence Intervals | 00:00:00 | ||
| One Sample T-Test | 00:00:00 | ||
| Two Sample T-Test | 00:00:00 | ||
| Two Sample T-Test Of Proportions | 00:00:00 | ||
| ANOVA | 00:00:00 | ||
Course Review
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Are you interested in higher education?
Great intro