I come from a pretty general one-year data science program. I frequently went beyond the classroom to learn. That’s no fault to the course at all. Most times it was because the topic was interesting and I wanted to learn more.
It led me to develop this blog with other ambitious students. It’s been a ride so far. But others looked at the course requirements and did what was asked of them and I hear them remark:
“I learned all that was asked of me, why do I feel unqualified to be a Data Analyst?”
As soon as the guidelines disappear, they lost structure to their learning. Do yourself a favour: become an agile data scientist and constantly improve your toolbelt.
“But how? And with what?”
I want to share with you what I use — two feeds, one learning website, and a local networking site.
I love Twitter. I’ve had been a user for seven years. I originally sprinkled data science influencers into my already existing feed, but I basically use the @DataCritics account now as a pure data science resource pool.
Dear Twitter network! @RLadiesLondon are organising first #rstats hackathon & are looking for a host who could offer a venue in central #London (capacity 40-50 ppl) + food & drinks. We’re aiming at running it in Sept. Let me know if you can you help or know someone who can! thx! pic.twitter.com/6httAALfsd
— kasiek (@KKulma) June 21, 2018
Twitter is an awesome resource for a new data scientist. All the tweets are concise packets of information about anything from the general industry to specific techniques. You can even build influence yourself by sharing your own content and insights.
I find the synergy of having professional development sprinkled in with my other interests in the same feed doesn’t make it feel like a chore to look at.
Remember, follow more cool people when they are retweeted into your timelines; you’ll build a personalized list of data science awesomeness and digest more information than you could imagine.
Here’s a quick list of accounts I constantly bookmark. Share with us your favourites in the comment section!
Communities and Brands
Follow @R4DScommunity – #TidyTuesday founders and showcase all the visuals and code from participants using the Tidyverse packages
Follow @Rbloggers – compiles articles from rbloggers.com which are more ambitious for me to learn from. Usually modeling and new techniques
Follow @CrimsonHexagon – visualizes cultural happenings with NLP
Follow @DataProgress – politically charged visuals and storytelling using NLP
Follow @RLadiesGlobal – promote women and events organized to empower women in programming, look up Women’s Data as well to find local sects in your city
Follow @realpython – python articles and updates
Influencers
Medium
Medium has in-depth tutorials and is home to a fantastic community. Create an account and add interests that cater to data science AND the workplace.
The Data science topic is obvious, it has the languages you do know and all the languages you don’t — but that gets you interested in learning more to add to your toolbelt! Here’s an example with ggplot2 that showcases a typical data science article and how effective they are.
But remember, data science is not just coding. I happily read articles like Mistakes I Made As a Beginner Programmer.
I also look at many Productivity and Health articles to learn how to better respect my self. I wake up to a set of Blue (self-care), Green (long-term goals), and Red (vices) lists on my whiteboard full of activities I feel help me function better for today and tomorrow AND also keep myself accountable for when I’m being lazy.
I owe it all to Medium to add a healthy perspective to my life and you should too.
DataCamp
I happily plug DataCamp without receiving any compensation, I swear. It is my favourite resource to learn more data science techniques.
DataCamp is the premiere learning resource right now. Yes, it costs money but the expertise and gigantic library of courses are very, very worth it.
A quick summary:
- I love their built-in UI to code right in your browser and the incredibly vast course offerings in R, Python, and SQL — currently 129 available.
- They offer free premium access for classrooms and have their own community of articles/tutorials.
- They even have career tracks made up of 20+ courses to give you all the tools you’ll need to find a career in that field.
Worth every cent. Just look at DataCamp’s Trello Board and see all their upcoming content.
Meetup
So now that we have two feeds and a website to learn from, let’s look at a very simple way to network with other learners and experts.
Find meetups in your surrounding area and you can learn data science or just drop-in to general discussions in fields you are interested in – just about everything uses analytics, so network wherever you deem fit.
The best part: you are networking with other eager people in your local community. You can join their groups, establish yourself, and make some great contacts.
Some meetups cost money -usually those teaching a workshop – but most are free.
Go attend some talks, complete some workshops and network with others attending.
Heck, you can even make you own meetup and teach others. Instead, they’ll be networking with you!
I hope that’s enough to get you going for now…
Now, you have two great feeds, Twitter and Medium, for concepts, tools, and practical learning. One premium learning resource in DataCamp. And a place to network with people in your area with Meetup.
Now I have to ask you to share: what has helped you become a better data scientist?
We have a comment section right down there.
datacritics 
Are you kidding me, Jake? I am so in the same shoes. Just finished a one year Masters program in Data Analytics and currently feeling the heat. Thanks for this guide.
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