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Learn R with Raspberry Pi

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DataCamp

Price: FREE (or $568 per year)

Created by: datacamp.com

R is a language intrinsically linked to data and statistical analysis. Popular with scientists and number crunchers, it has fans around the globe.

If you’ve spent a lot of time in Python and other programming languages, some of the features of R are confusing at first. Assignment operators are arrows, and lists are one-indexed (with the first item starting at position one, rather than zero). All of this is designed to make working with large datasets more friendly.

DataCamp is a great learning resource for R, Python, and SQL. It uses a web-based code editor (which admittedly, we have mixed feelings about). The basic course is free, and you can pay for a DataCamp subscription to access a wide range of advanced courses. A subscription isn’t cheap though, coming in at over $568 per year, although there are frequent half-price sales and it is aimed at budding data scientists.

Datacamp helps you learn the statistic-focused language and is ideal for wannabe data scientists

Coursera

Created by: Duke University & John Hopkins University
Price: £38 / $49 (per month)

Coursera offers a range of courses from universities. There are two that should be of interest. The first is Introduction to Probability and Data from Duke University (magpi.cc/courseraprobability), with a 4.7 star rating. Led by Mine Çetinkaya-Rundel, Associate Professor of the Practice Department of Statistical Science, the course features R, but it’s more about learning to crank data. It gives you a grounding in probability and Bayes’ rule. It covers sampling methods, and forms part of a larger Statistics with R Specialization, which you can take to learn more about R.

The second suggested course is R Programming from John Hopkins University (magpi.cc/courserar). This will get you closer to the R language.
After a seven-day free trial, you’ll pay Coursera a monthly fee to access the courses.

Coursera provides access to online learning tools provided by respected academic institutions

Introduction to R for Data Science

Created by: Microsoft

Price: FREE ($99 certificate)

We’re big fans of the edX platform, which offers a range of courses from respected universities and organisations. Its Introduction to R for Data Science course is provided by Microsoft and runs on the DataCamp platform (so it’s an interactive web approach). This is interspersed with video tutorials and short online quizzes. The edX community is vibrant, with an active forum that is ready to answer any questions you might have.

It’s an accessible course and, thanks to being on edX, you can enrol and take the course for free. You only need to pay to get a certificate at the end.

The edX platform offers curated learning content from the likes of Harvard, MIT and Microsoft

R websites

Bookmark these webpages while learning R.

R-bloggers

R-bloggers is a website aggregator for blogs on R. In it, you’ll find the latest contributions from hundreds of different R bloggers.

Keep abreast of what's being posted online about R with the R-blogger content aggregator

R-exercises

R-exercises aims to help people develop and improve their R programming skills. R-exercises was initiated and is maintained by Research for Decisions, a Dutch research and consulting firm.

Revolutions

Revolutions (blog.revolutionanalytics.com) is a blog dedicated to news for the R community. It’s a great place to find out recent developments and news.

Data sources

Data

The US and UK governments have made huge datasets open. Everything from business figures to the environment, through mapping and spending, can be found online at
data.gov.uk.

The UK and US governments publish vast data sets you can use. UK ones can be found at data.gov.uk

Kaggle

Kaggle is an online community owned by Google. It’s a great resource for datasets, as well as featuring blogs, competitions, and tools.

Dataquest

There’s a range of datasets around, from Google, Wikipedia, and Amazon, and even news outlets such as BuzzFeed. Dataquest has a great list of sources for you to bookmark.

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