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It seems like every day there are new advances in data science and it feels important for our careers. With so much going on, it's pretty clear that we need to stay on top of our games every day, but it's hard to do.
Sure, we can learn all of these skills ourselves. but it's hard to understand everything that's coming out and what to focus on. This is where communities shine, helping us stay informed about new knowledge needed for our careers.
Many smaller and larger data science communities could help improve our careers. But, if you only have time to spend in five different communities, these are the ones you should focus on.
Let us begin.
Let's start with the one that seems casual, which is Reddit.
Yes, Reddit is a social media forum famous for its memes and random discussions about life. However, it is still a social media platform with a bulletin board structure that generates many informal discussions. One of them is for data science.
In reality, Reddit is packed with activities for any data science enthusiast and professional. The important thing is to find specific communities within Reddit that can facilitate our learning.
For that I recommend joining the r/data science community, which has 1.4 million members and has new discussions daily. Almost every day there was a discussion on data science topics. From casual questions to advanced career advancements, the community is lively to chat with everyone.
Besides, r/machine learning is a great community to join if you want to discuss specific machine learning topics with over 2.9 million members.
The next community you should join is Kaggle.
I'm sure many of you who have started learning data science have heard of it. But if you've never heard of Kaggle, it's a platform for sharing and publishing datasets, exploring and building machine learning models on your laptop, and sharing all of our data work. It is also the hub of data science competition as many companies conduct online competitions on this platform.
Kaggle's premise is to share our work in data science with the public, so it has become a central place for many people who work with data to communicate. I have already received so much help from the local community for my personal and professional work that I feel it is one of the best communities out there.
This is because many useful advancements and information are implemented there, which is a great way to learn new skills to advance your career. Additionally, many professionals and experts contribute a lot to the community for free.
The Kaggle community is open to any level of your data career. Whether you're a beginner professional or a competitive champion, the Kaggle community is there to help you.
For some people, LinkedIn is the place to look for a new job or learning platform. However, it is still social networks at the core.
LinkedIn allows its users to create community groups where like-minded people can post and share their thoughts. One of the largest data science community groups on LinkedIn is the Data Science Community (Moderated) by Robbert van Vlijmen, which has more than 500,000 members.
Members often share useful learning material and provide a place where you can ask any question, regardless of your professional level. So don't feel pressured if you think the discussion seems too difficult to follow.
Another LinkedIn group I recommended joining is the KDnuggets Data Science and Machine Learning (Moderate). With over 150,000 internal members, there is a daily member post to help you learn, including the latest KDNuggets article, which you can discuss internally.
KDNuggets LinkedIn Group Community (Image by author)
Several other communities with many members that are still related to data science, including:
He DataTalks.Club is a community for data enthusiasts by Alexei Grigorev.
It is a community designed to discuss any data topic, from data analytics, machine learning, and data engineering to data science. Whatever data questions you have, the community is ready to answer them.
However, the best part about this community is that you can discuss any topic related to your career, like deciding your next step or what to learn. If you want to interact with the community, joining the DataTalks Slack channel is a great way to continue discussing.
The community also has an abundant event that you can join. You can join the community learning for free, from one-off minor events to free bootcamps. These free boot camps are certainly famous because they give you free enterprise-level skills that you might have to pay a lot of money for elsewhere.
Plus, there are podcasts and book discussions you can learn from. The point is that this community is actively trying to make you a better person in your data career.
The last community that I recommend to advance your career is the MLOps Community.
MLOps Community (Image by author)
So listen to me. The community may not necessarily be specific to data science, as MLOps is part of data science. However, a successful data science project is where we can provide ongoing value to the business, and MLOps provides that.
That's why I recommend the MLOps community as a place that could help you in your future career. I also say this because MLOps is becoming a skill that many data science jobs are trying to pursue.
The community, especially Slack, is active with lots of conversations about MLOps and sometimes general discussion. However, I gained a lot of knowledge there, and you should too.
The data science community plays an important role in advancing our careers. By interacting and learning from others, we can understand many new things that we could not achieve before. There are many data science communities out there, but here are five communities you should join:
- Kaggle
- Data Talks
- MLOps Community
I hope that helps! Share your thoughts on the communities listed here and add your comment below.
Cornellius Yudha Wijaya He is an assistant data science manager and data writer. While working full-time at Allianz Indonesia, she loves sharing Python tips and data through social media and print media.
