🎓 data science for openwashdata - 002

We're doing it again! Two years after our first iteration, we're running the "data science for openwashdata" course again.

The course content will largely stay the same with a few distinct differences:

1. We will provide recordings of the live lectures, but expect you to complete a new homework quiz within two weeks after the lecture.

2. We will teach the bonus module: "Use of AI for coding support".

3. We are starting a mentorship programme for increased learning and support.

4. We offer language support for Spanish speakers.

🚀 You can't wait?

Sign-up here (it will take you 15 minutes): https://ee-eu.kobotoolbox.org/x/7V3qeDYD

📚 You need more info?

Find the course website here: https://ds4owd-002.github.io/website/

📊 You're interested in some statistics from the first iteration?

Read Adriana's blog post: https://openwashdata.org/pages/blog/posts/2025-07-07-ds4owd-001-analytics

🤔 Who can participate?

To participate in this course, you need to:

• be somewhat connected to the greater Water, Sanitation and Hygiene (WASH) sector (yes, public health, solid waste management, global health engineering, and related topics also count)
• commit 9 × 2.5 hours to participate in Zoom calls
• commit another 3 hours/week for readings and additional exercises for practice
• identify a dataset of your own or your organization that you're interested in sharing with the publicb
• have an openness to new ideas and workflows that disrupt current practice

🎁 What do we offer?

This course is:

• Free and accessible to all
• Certificate provided for successful completion
• Open source - uses exclusively free and open source tools
• Personalized support - 1:1 coding sessions between lectures and beyond
• Project-focused - build a portfolio of real-world data analyses
• Community-driven - join the openwashdata community of practice

📢 Spread the word!

If you know someone who might be interested in this course, please forward this email to them or share the course website: https://ds4owd-002.github.io/website/