- Course type
- Paid course
- All Levels
- 7 hours
- 126 lessons
- Available on completion
- Course author
- 365 Careers
- Learn the fundamentals of programming in R
- Work with R’s conditional statements, functions, and loops
- Build your own functions in R
- Get your data in and out of R
- Learn the core tools for data science with R
- Manipulate data with the Tidyverse ecosystem of packages
- Systematically explore data in R
- The grammar of graphics and the ggplot2 package
- Visualise data: plot different types of data & draw insights
- Transform data: best practices of when and how
- Index, slice, and subset data
- Learn the fundamentals of statistics and apply them in practice
- Hypothesis testing in R
- Understand and carry out regression analysis in R
- Work with dummy variables
- Learn to make decisions that are supported by the data!
- Have fun by taking apart Star Wars and Pokemon data, as well some more serious data sets
R Programming for Statistics and Data Science 2022
R Programming is a skill you need if you want to work as a data analyst or a data scientist in your industry of choice. And why wouldn't you? Data scientist is the hottest ranked profession in the US.
But to do that, you need the tools and the skill set to handle data. R is one of the top languages to get you where you want to be. Combine that with statistical know-how, and you will be well on your way to your dream title.
This course is packing all of this, and more, in one easy-to-handle bundle, and it’s the perfect start to your journey.
So, welcome to R for Statistics and Data Science!
R for Statistics and Data Science is the course that will take you from a complete beginner in programming with R to a professional who can complete data manipulation on demand. It gives you the complete skill set to tackle a new data science project with confidence and be able to critically assess your work and others’.
Laying strong foundations
This course wastes no time and jumps right into hands-on coding in R. But don’t worry if you have never coded before, we start off light and teach you all the basics as we go along! We wanted this to be an equally satisfying experience for both complete beginners and those of you who would just like a refresher on R.
What makes this course different from other courses?
Receive top class training with content which we’ve built - and rigorously edited - to deliver powerful and efficient results.
Even though preferred learning paces differ from student to student, we believe that being challenged just the right amount underpins the learning that sticks.
Introductory guide to statistics.
We will take you through descriptive statistics and the fundamentals of inferential statistics.
We will do it in a step-by-step manner, incrementally building up your theoretical knowledge and practical skills.
You’ll master confidence intervals and hypothesis testing, as well as regression and cluster analysis.
The essentials of programming – R-based.
Put yourself in the shoes of a programmer, rise above the average data scientist and boost the productivity of your operations.
Data manipulation and analysis techniques in detail.
Learn to work with vectors, matrices, data frames, and lists.
Become adept in ‘the Tidyverse package’ - R’s most comprehensive collection of tools for data manipulation – enabling you to index and subset data, as well as spread(), gather(), order(), subset(), filter(), arrange(), and mutate() it.
Create meaning-heavy data visualizations and plots.
Practice makes perfect.
Reinforce your learning through numerous practical exercises, made with love, for you, by us.
What about homework, projects, & exercises?
There is a ton of homework that will challenge you in all sorts of ways. You will have the chance to tackle the projects by yourself or reach out to a video tutorial if you get stuck.
You: Is there something to show for the skills I will acquire?
Us: Indeed, there is – a verifiable certificate.
You will receive a verifiable certificate of completion with your name on it. You can download the certificate and attach it to your CV and even post it on your LinkedIn profile to show potential employers you have experience in carrying out data manipulations & analysis in R.
If that sounds good to you, then welcome to the classroom :)