Thank you for joining our community! We hope you’ll like it here.
DataTalks.Club is a place to talk, learn, discuss, and share. To make our discussion more organized, we need to follow community guidelines.
Table of contents:
Code of conduct
Be respectful and remember that there’s a human on the other side of the screen. We do not have our own code of conduct, but we follow the Python Software Foundation one. Please read the “Inappropriate Behavior” section.
Some examples of inappropriate behaviour:
- Judging the question or the person asking the question (“this is a stupid questions and everyone who can read docs knows the answer”)
- Soliciting any kind of personal information (such as marital status, sexual orientation, phone number, address, etc)
- Continued one-on-one communication after requests to cease
Taking part in discussions
Do not double post — select the best channel for your message and post it only once.
Avoid asking questions in DM. If you ask your question in a public channel, others will also benefit from the answers.
Use threads. They help to keep the discussions more organized.
Thread best practices:
- Don’t break your question into multuple messages. Put everything in one.
- For long questions, write a few sentences in the first message, and put the rest in a thread.
- If there’s a code snippet (more than 5 lines of code), put it inside the thread.
- Avoid using the “also send to channel” feature unless it’s really necessary.
- If your question contains multiple questions, make sure to break them into multiple messages, so each could be answered in a separate thread.
Avoid meta-questions. Meta questions are questions about asking questions.
- Can I ask a question about data science here?
- Yes, you can! That’s the reason this slack exists!
- Is there anyone who knows marketing? I have a question about it.
- Yes. Just ask your question about marketing - or anything else - directly.
- Has anyone done Machine Learning Zoomcamp? I have a question about it.
- Just ask the question. If somebody has done it, they’ll answer.
- The same applies to books and anything else.
Some other tips:
- If you want to start a discussion, don’t just share a link and expect others to jump in. Share your thoughs and have a clear question in your message.
- “Any thoughts on this?” is not a clear question.
- Be consice in your questions if possible. Not everyone likes to read a lot of text.
Use channels when possible. For example, instead of using
#general for asking a question about machine learning, use
#announcements— for community-wide announcements
#general— for general discussions
#shameless-promotion— for promoting your work (see the promotion section for more information about promoting your work)
#book-of-the-week– to talk about books with book authors (check the books page for more information)
#career-questions– for career discussions (switching from one role to something data-related, being better at work, etc)
#datascience– for talking about data science, machine learning, algorithms, training process, and ml-related libraries
#engineering– for discussing the engineering aspects of data science: data engineering, ML engineering, MLOps, and so on
#events– to talk about events (not just our events, but events in other communities as well)
#jobs– for jobs
#random– for chit-chat about pretty much anything
This is not a complete list of channels. To check the list of all the available channels, use this: https://slack.com/intl/en-de/help/articles/205239967-Join-a-channel
Promoting your work is welcome — for both companies and individuals. We have a special channel
for that —
#shameless-promotion. You can use it for sharing social media links, blog posts,
and anything else. Please don’t use other channels for that.
Surveys and feedback on your product
Messages that ask the community for feedback on your product are considered promotional as well
and should be posted in
- We’re conducting a survey to better understand how people use
- We’d like to show you our product and get some feedback from you.
- We’re working on
____and would like to talk to data scientsits and ML engineers to understand better their painpoints.
To promote your events, you can share them in
#shameless-promotion is also fine.
Rules for vendors
If you represent a company, indicate your affiliation if you suggest using your services when answering questions.
We do not welcome unsolicited promotional messages in DM. Violating it will result in a ban.
Instead, use the
#shameless-promotion channel, and if somebody is interested in your product or service,
they will reach out to you.
If you get unsolicited promotional messages in DM, report it to Alexey Grigorev.
Note that promoting yourself and your services is also a promotion. For example, mass-sending your CVs in DMs is also considered unsolicited promotion, and the same rules apply.
Promotional messages have to be relevant for the community. If it’s not relevant, don’t post them.
Examples of not relevant promotional messages:
- COVID surveys for $5
- Coupon codes for lawn mowers or pizzas
If you’re looking for colleagues, use the
To make it easier for others to judge if a position is relevant for them, please mention:
- City / Country
- Relocation support
- Possibility to work remotely
And don’t forget to include contact details and the link to the job description :)
Since we’re a data community, please make sure the positions are related to data or to software development.
Examples of relevant positions:
- Data/product analyst
- Data scientist
- Machine learning engineer
- Data engineer
- Analytics engineer
- Developer advocate
- Software engineer / Python developer
Examples of not relevant positions:
- Accountants and bookkeepers
In general, we’d be happy to help with your homework, provided that you show genuine effort from your side and you are clear about the source of your question.
Copy-pasting an exercise and expecting others to jump in and solve it for you might be a long shot — don’t be surprised if nobody answers. To increase your chances of getting an answer, consult this answer from StackOverflow.
The same applies to interview take-home assignments. We’re happy to help, but be transparent about it.