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(This article was first published on <strong><a href="http://itsalocke.com/getting-started-with-data-science-recommended-resources/"> R – Locke Data</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>An oft asked question is what resources can I recommend for getting started with data science? Here are my recommendations, and if you have others, please put them in the comments!</p>
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NB Links in this post may be affiliate links – it doesn’t change the prices you get but might earn me a little money
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<h2>Books</h2>
<h3>Data Science for Business</h3>
<figure class="wp-caption"><a target="_blank" rel="nofollow" href="http://geni.us/dsforbiz"><img sizes="(max-width: 228px) 100vw, 228px" alt="Data Science for Business" class="wp-image-62171" src="https://i1.wp.com/itsalocke.com/wp-content/uploads/2017/05/dsbiz-228x300.png?resize=228%2C300" data-recalc-dims="1"></a><br>
<figcaption class="wp-caption-text">Data Science for Business</figcaption>
</figure>
<p><a target="_blank" rel="nofollow" href="http://geni.us/dsforbiz">Data Science for Business</a> is a great overview book.</p>
<p>It’s not very technical and it makes the concepts very accessible. I especially found the sections describing how loss functions work, particularly enlightening compared to other explanations I’ve seen.</p>
<p>Most importantly, it dwells on the process and the business implications of data science. This is a book I’m happy to recommend to managers, technology people, and recent graduates alike.</p>
<p>I read the book on my phone on kindle, usually when I was travelling. It remained something readable and intelligible at early hours and late nights – a compelling endorsement in an area where the books can be dense and make one’s brain bleed out of one’s ears. </p>
<h3>R for Data Science</h3>
<figure class="wp-caption"><a target="_blank" rel="nofollow" href="http://geni.us/rfords"><img sizes="(max-width: 200px) 100vw, 200px" alt="R for Data Science" class="wp-image-62172" src="https://i0.wp.com/itsalocke.com/wp-content/uploads/2017/05/cover-200x300.png?resize=200%2C300" data-recalc-dims="1"></a><br>
<figcaption class="wp-caption-text">R for Data Science</figcaption>
</figure>
<p><a target="_blank" rel="nofollow" href="http://geni.us/rfords">R for Data Science: Import, Tidy, Transform, Visualize, and Model Data</a> is written by <a target="_blank" rel="nofollow" href="https://github.com/hadley">Hadley Wickham</a> and <a target="_blank" rel="nofollow" href="https://github.com/garrettgman">Garett Grolemund</a>. You can <a target="_blank" rel="nofollow" href="http://geni.us/rfords">buy</a> it and you can also access it <a target="_blank" rel="nofollow" href="http://r4ds.had.co.nz/">online</a>.</p>
<p>If you’re interested in learning to actually start doing data science as a practitioner, this book is a very accessible introduction to programming.</p>
<p>Starting gently, this book doesn’t teach you much about the use of R from a general programming perspective. It takes a very task oriented approach and teaches you R as you go along.</p>
<p>This book doesn’t cover the breadth and depth of data science in R, but it gives you a strong foundation in the coding skills you need and gives you a sense of the of the process you’ll go through.</p>
<p>I really like this book but it’s important to note you may have some gaps in your knowledge if this is your main introduction to R programming.</p>
<h3>Introductions to R</h3>
<p>There are many introductions to R that are useful. The difficulty lies in that there aren’t many focusing on modern R.</p>
<p>I struggle with the ongoing debate about whether I teach people a strong understanding in base R (or vanilla R) or do I teach them modern R (e.g. data.table and the tidyverse) which I perceive to be easier?</p>
<ul>
<li>Base R is quirky and quite difficult to learn. Modern R is much easier. </li>
<li>Base R knowledge ensures you understand the core objects and programming constructs. Modern R focusses on tabular data, which is what most people need.</li>
<li>Base R is stable. Modern R is bleeding edge.</li>
</ul>
<p>There are very good base R introductory books but we’re still relatively lacking in ones that incorporate a lot of modern R.</p>
<ul>
<li><a target="_blank" rel="nofollow" href="http://geni.us/introRvenables">An Introduction to R</a></li>
<li><a target="_blank" rel="nofollow" href="http://geni.us/rcookbook">R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics</a></li>
<li><a target="_blank" rel="nofollow" href="http://geni.us/tyr24">Teach Yourself R in 24 Hours</a> (modern R-ish)</li>
</ul>
<h2>In-person</h2>
<h3>User groups</h3>
<p>User groups are a great way to meet people in the field and see some talks in the area. For the most part, I recommend you go to <a target="_blank" rel="nofollow" href="https://meetup.com/">meetup.com</a> and look for local data science, python, or R meetups near you.</p>
<p>I love user groups and I think they’re a great way to build a local network of people you can chat to about your start in data science.</p>
<h3>Training</h3>
<p>There’s a reasonable amount of people out there offering introductions to R and data science. I myself offer training, from bespoke to <a target="_blank" rel="nofollow" href="https://itsalocke.com/community-r-workshops/">community workshops</a> to <a target="_blank" rel="nofollow" href="https://itsalocke.com/r-for-bi-people/">training for BI people</a>. You can often search <a target="_blank" rel="nofollow" href="https://www.eventbrite.com/">Eventbrite</a> or ask on twitter to find an event happening near you. Your local user group is another great place to ask.</p>
<h3>Conferences</h3>
<p>You can also check out a lot of conferences. KDNuggets keep a good <a target="_blank" rel="nofollow" href="http://www.kdnuggets.com/meetings/">list of conferences</a> that you can attend.</p>
<p>As data science is becoming so popular, you can often see a lot of data science appearing in non-data science conferences, especially data platform and analysis conferences so you might be able to look to conferences you already know about for getting started with data science.</p>
<h2>Online</h2>
<h3>Blogs</h3>
<p>I love reading blogs as a way of learning in an area – not only do you get technical knowledge but people are kind enough to share theory and current trends too. I read a variety that might not suit everyone but if you’re just starting out I recommend <a target="_blank" rel="nofollow" href="https://github.com/rushter/data-science-blogs">Becoming a Data Scientist</a> and <a target="_blank" rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers</a>.</p>
<h3>Online practice</h3>
<p>Getting hands-on is an important aspect of learning for me.</p>
<p>A great way to start doing that in, a very chuck yourself in at the deep end kind of way, is to start learning on <a target="_blank" rel="nofollow" href="https://kaggle.com/">Kaggle</a> and especially their <a target="_blank" rel="nofollow" href="https://www.kaggle.com/c/titanic">Titanic competition</a>.</p>
<p>In more gentle ways of learning, you can start using Microsoft <a target="_blank" rel="nofollow" href="https://studio.azureml.net/">free notebook and machine learning platform</a> to start coding things.</p>
<h3>Podcasts</h3>
<p>Alas, I’m not a podcast person so I’ve only one recommendation for you: <a target="_blank" rel="nofollow" href="https://soundcloud.com/nssd-podcast">Not So Standard Deviations</a>.</p>
<h3>DataCamp</h3>
<figure class="wp-caption"><a target="_blank" rel="nofollow" href="https://www.datacamp.com/"><img sizes="(max-width: 300px) 100vw, 300px" alt="DataCamp" class="wp-image-62173" src="https://i0.wp.com/itsalocke.com/wp-content/uploads/2017/05/logo_vertical_dark-99c0154ba9bd796df65021826de1b4d4aa475eeb0134504dd05d6bc5a8d31b07-300x214.png?resize=300%2C214" data-recalc-dims="1"></a><br>
<figcaption class="wp-caption-text">DataCamp</figcaption>
</figure>
<p>By far my most recommended site for learning R and data science is <a target="_blank" rel="nofollow" href="https://www.datacamp.com/">DataCamp</a>. DataCamp blends videos and online exercises making it a great way to learn practically but still get the theory.</p>
<p>There are a number of free introductory courses, but DataCamp works on a monthly subscription access model of $29. For the monthly fee, you can consume any and all of their courses.</p>
<p>DataCamp is great value for money, especially if you want to do an intensive month of learning and then end your subscription.</p>
<h3>Coursera</h3>
<figure class="wp-caption"><a target="_blank" rel="nofollow" href="https://click.linksynergy.com/fs-bin/click?id=vnlIMjYGRYA&offerid=467035.210&%23038;type=3&%23038;subid=0"><img sizes="(max-width: 300px) 100vw, 300px" alt="Coursera" class="wp-image-62177" src="https://i0.wp.com/itsalocke.com/wp-content/uploads/2017/05/logo_square-300x300.png?resize=300%2C300" data-recalc-dims="1"> </a><br>
<figcaption class="wp-caption-text">Coursera</figcaption>
</figure>
<p><a target="_blank" rel="nofollow" href="https://click.linksynergy.com/fs-bin/click?id=vnlIMjYGRYA&offerid=467035.210&type=3&subid=0%22">Coursera</a> is the original online course provider.</p>
<p>They’ve got some fantastic courses for getting started with data science.</p>
<p>With online courses like this, you can find yourself dropping off it and not finishing a course. I recommend you start with just a course or two before you go for something like the <a target="_blank" rel="nofollow" href="https://www.coursera.org/university-programs/masters-in-computer-data-science">$20k Masters in Data Science</a> that you could work towards on there!</p>
<p>The post <a target="_blank" rel="nofollow" href="http://itsalocke.com/getting-started-with-data-science-recommended-resources/">Getting started with data science – recommended resources</a> appeared first on <a target="_blank" rel="nofollow" href="http://itsalocke.com/">Locke Data</a>. Locke Data are a data science consultancy aimed at helping organisations get ready and get started with data science.</p>
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