Must-Read Blogs for Data Scientists :
By: M Usama
Tags: Big Data, Data Science, Professional Writing, Copywriting, Machine Learning

Welcome to 2020! A new year and a new decade. As we begin a new and exciting year in data science, it is important that professionals discover the top data science blogs to follow in 2020 to keep up on the important trends and developments.

The data scientist profession saw an increase of 56% in job openings between 2018 and 2019. It was the most promising job of 2019 and will remain in high demand throughout 2020 as more businesses invest in data projects.

A new and exciting year is just beginning for data science, and we can’t wait to see which trends will shape the industry and which innovations will take data science further than ever before.

Beginners New to Data Science :

What’s the big data?

What’s The Big Data? is where business breakthroughs, investments, and data science collide. Read about new data theories, suggestions for big data management, and anything that helps evolve the IT/ data landscape. The blog was created by Gil Press, a former Senior Director in Thought Leadership Marketing at Dell EMC for over 16 years and current Managing Partner at the press, marketing, publishing, and research consultancy. If you’re interested in becoming a data scientist, this is also a good blog to check out because of the Q&A interviews with top data scientists in the industry. Current data science students:

r/datascience :

If you’re studying data science and you’re not part of Reddit’s Data Science community, you’re missing out on a ton of valuable info and communication with people just like you. Get must-read advice on interview prep, check out an ever-expanding world of resources, find the answers to knotty problems, debate the usefulness of various tools in learning and so much more. With over 208,000 members, it’s an unmissable asset — as long as you’re prepared to lose more than a few hours lost in the discussion.

FlowingData :

If you’ve kicked off your learning, you’ll know that one of the more interesting parts of data science study is building out visualizations. FlowingData author Nathan Yau, who holds a Ph.D. in statistics from UCLA, has been dedicating much of his time to building out COIVD data sets, looking at changes in airline flights, how social distancing works (and doesn’t), how stay-at-home orders change from region to region and more. Subscribers can also pay to unlock ‘The Process’, a newsletter filled with useful activities and lessons in modeling.

Kaggle :

Read about how a data scientist was hired at Airbnb, how banking and financial services fields scale their automation by using machine learning, all the way to recommendations on first data subjects to learn about in Data Science Report. Since the publishers, Starbridge Partners — a specialty executive search firm, are skilled in helping professionals land new careers, you can also find a solid data science job listings resource for once you finish studying.

Revolution :

If you’re an R advocate, the Revolutions blog is for you. The site is updated almost every day and is can’t miss if you’re passionate about Python, machine learning, and visualizations. It’s the place to go for weekly roundups on the latest software updates and insight into what’s going on in the industry, plus it has a frequently updated list of resources to help you as you learn. There’s also an extremely robust user directory, so you can find the data science group, and topic, you’re most passionate about — or you can start one of your own.