R Programming for Data Science & Data Analysis. Applying R for Statistics and Data Visualization with GGDescription2 in R

R Programming for Statistics and Data Science - NEW 365 Careers content --

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?

Well-paced learning.

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 Descriptions.