Upskilling and reskilling are critical for those in the social sector looking to be more engaged with data. What have you observed about programs that do this effectively?

As someone who teaches courses on technology, I can tell you that even the best universities have struggled to teach data science at all levels.  

Upskilling and reskilling are really key to a professional “data for good” journey, but it’s hard work. 

This field is still young and there isn’t a great roadmap for trying to apply data science to social impact challenges like climate change, food scarcity, disease spread, etc. These are complex problems and the data science tools and approaches that exist are all fairly new, relatively speaking. 

Here are a few things that I think make for great programs:

1. They keep pace. The data science landscape is changing really fast. The rise of AI, for instance, is already having tremendous impacts on coding and data science and changing the hard skills that practitioners need to be successful in their work. 
2. They balance the technical and non-technical aspects. Technology moves faster than our ability to create systems and frameworks for governance, ethics, equity, regulation, and more. Great programs embrace this and focus as much on “softer” skills like responsible data use. 
3. They focus on relationship building and provide hands-on opportunities to collaborate with non-profits, governmental agencies, and other social sector organizations. These kinds of partnerships can offer practical insights, access to data, and opportunities for students to see the direct impact of their work. 

Hope this helps and best of luck to those on this journey—it’s a deeply rewarding one and your skills are greatly needed!

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