We will take you through descriptive statistics and the fundamentals of inferential statistics. Receive top class training with content which we’ve built – and rigorously edited – to deliver powerful and efficient results.Įven though preferred learning paces differ from student to student, we believe that being challenged just the right amount underpins the learning that sticks. What makes this course different from other courses? 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. This course wastes no time and jumps right into hands-on coding in R. 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’. 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. So, welcome to R for Statistics and Data Science! This course is packing all of this, and more, in one easy-to-handle bundle, and it’s the perfect start to your journey. Combine that with statistical know-how, and you will be well on your way to your dream title. R is one of the top languages to get you where you want to be. And why wouldn’t you? Data scientist is the hottest ranked profession in the US.īut to do that, you need the tools and the skill set to handle data. 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. R Programming for Statistics and Data Science 2020
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All software and data used in the course are free.
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We will show you how to do it in one of the first lectures of the course Have fun by taking apart Star Wars and Pokemon data, as well some more serious data sets.Learn to make decisions that are supported by the data!.Understand and carry out regression analysis in R.Learn the fundamentals of statistics and apply them in practice.Transform data: best practices of when and how.Visualise data: plot different types of data & draw insights.
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