Let's contribute to scikit-learn and Fairlearn! Mentored workshop

PyLadies Berlin are excited to bring you this open source workshop dedicated to contributing to scikit-learn and Fairlearn!

scikit-learn is a popular machine learning library and is widely adopted in industry as well as academia.

Fairlearn is a community-driven project to help data scientists improve fairness of AI systems.

In this session, you will be guided on how you can make your own contributions to the projects, no prior experience in contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted! If you don’t finish your contribution during the event, we hope you will continue to work on it after the workshop. The mentors will be available for help online after the event.

• Format for the session:
6:30 - 6:45 pm: Welcome, networking, food and drinks
6:45 - 6:50 pm Community announcements
6:50 - 7:00 pm: Introduction to scikit-learn - what you can contribute and how to contribute
7:00 - 7:10 pm: Introduction to Fairlearn - what you can contribute and how to contribute
7:10 - 9:45 pm: "Office hours" during which you'll be mentored for making a contribution to scikit-learn or Fairlearn.
9:45 - 10 pm: Wrap up and good bye.

**Pre Workshop Session**
For attending the event it is required that you have successfully installed the dev version of scikit-learn or Fairlearn, have set up a dedicated python environment for the project you want to work on, and that tests are running successfully. We have a dedicated pre-workshop event scheduled for these tasks which will be happening on 12 February. It is mandatory to sign up for this event if you don't have a working development environment. You can install all requirements for scikit-learn yourself by following steps 1 to 7 under "How to contribute" here. Note that during the main workshop, we won't have the resources to help you set up your environment.

❓ Can men attend ❓
Everyone is welcome. If you identify as someone well-represented in open source and in tech, please be mindful of the space and privileges you have, and use it to support others.

• Audience level
Everyone is welcome to attend this session! If you've never contributed to open source software before, then you will learn how to, and if you have experience in contributing, then you can either help mentoring other attendees or you can work on more challenging contributions. It is useful to have some scikit-learn, git, and python experience.

• Facilitators
The session will be lead by Maren Westermann (PyLadies Berlin, scikit-learn team member), Tamara Atanasoska (scikit-learn contributor, Fairlearn maintainer), Stefanie Senger (scikit-learn team member), Adrin Jalali (scikit-learn and Fairlearn maintainer) and Guillaume Lemaitre (scikit-learn maintainer).

• Host
This event is being sponsored by [Probabl.ai](https://probabl.ai/)
Food and drinks will be available by our hosts 🥳

• By attending our event, you agree to the PyLadies Code of Conduct:[ https://www.pyladies.com/CodeOfConduct/](https://www.pyladies.com/CodeOfConduct/)

• Contact
Interested in speaking at one of our events? Have a good idea for a Meetup? Get in touch with us at berlin@pyladies.com
Find us on the PyLadies Global workspace:
1. https://slackin.pyladies.com enter your email address.
2. Accept the email invitation
3. Go to workspace https://pyladies.slack.com
4. Join channel #city-berlin, #germany, #jobs-europe