In This Article
Whether data drives your marketing strategies or powers complex climate simulation models, the goal remains the same: uncovering and extracting actionable insights that make a real impact. In a world where data is everywhere and the demand for data science expertise is outpacing supply, staying sharp and up to date has never been more important. Whether you’re a seasoned analyst or just starting out, keeping your skills fresh is key to staying relevant in this fast-evolving field. So, we’ve rounded up some of the best blogs on the web to help you stay at peak analytical fitness.
R-bloggers
R is possibly the most powerful and widely used statistical, machine learning and data visualization programming language. As the emerging data scientist’s tool of choice, R-bloggers brings together a vast community of R users in what they call the “R blogosphere”. If Internet marketing is your game and you’re knee-deep in clickstream data, then check out their blog on how to get R talking to the Google Analytics API: https://www.r-bloggers.com/using-google-analytics-with-r/.
KDnuggets
Walkthroughs of popular topics within data science like Bayesian analysis and deep learning, while still managing to keep it fairly accessible as well as intelligent related articles about the field. They even provide links to datasets so you can exercise your data mining and data science expertise.
Coursera
There are plenty of free, online and excellent learning resources including FutureLearn, Standford Online, iversity and edX. One that I have found particularly useful at getting a handle on a number of statistical and analytical areas is Coursera. They have a wide variety of data science specialism courses, most of which you can take completely free, coursework and peer assessment included.
MIT OpenCourseWare on YouTube
https://www.youtube.com/channel/UCEBb1b_L6zDS3xTUrIALZOw
This YT channel is an excellent resource for learning the more tech-heavy computer science concepts for anybody from entry level analysts to seasoned miners looking to refresh their knowledge of search algorithms. A virtual seat in full-length lectures of one most prestigious technology educators. A number of other institutions also provide similar resources so explore!
The r/datascience, r/MachineLearning and r/bigdata Subreddits are also some useful corners of the web to keep an eye on for current developments, learning resources, recommendations and discussion threads. Sometimes responses may be relatively thin on the ground compared to, say, posts speculating the next death on The Walking Dead but gems aren’t so rare. There’s also a ML @ Reddit (@mxlearn) Twitter account, which posts research, news and discussions pretty regularly.
Data Tau
Definitely bookmark this one. The most up-to-date data news and discussions, sort of similar to KDnuggets, covering many different topics and updated very frequently. An extremely valuable well of information and a handy supply chain for the data scientist’s online library.
X
Lastly, X is also another great place to keep up to date with developments in the field as well as thought pieces from data scientists working in all fields, like ex-professor of astrophysics Kirk Borne (@KirkDBorne), to help inspire your analysis with some newfound flair.
Want to turn data into real marketing results? Found’s data science team combines advanced analytics with strategic insight to drive smarter, faster growth.
