Why Global Teaching Fellows?

We just opened up our Global Teaching Fellows program. This is a big change from requiring that all our teaching fellows are local in the Bay Area. We wanted to explain why we made this change and what makes us excited about the 2020 teaching fellow program.

Delta Analytics is a 501(c)(3) nonprofit organization that was founded 6 years ago with a focus on helping nonprofits and social impact organizations leverage their data for good.

Three years ago, Delta Analytics started a Teaching Fellows Initiative. The goal of the program is to build technical capacity around the world. In 2017, we developed our pilot course, which focused on explaining the fundamentals of machine learning.

We brought our first program to Nairobi, Kenya, partnering with the Moringa School for our pilot class. We decided early on that teaching machine learning with relevant local data was critical. Leveraging local data emphasized that the students were the domain experts, and empowering students to feel confident with feature engineering is a practice we have carried forward.

For the pilot, we partnered with Kiva.org to use a dataset of Kenyan loans over a 12-year period; in following iterations, we encourage students to work with local data or to solve problems relevant to their interests.

In 2018, we partnered with Kiva.org to teach the curriculum to non-profit professionals in San Francisco as a series of lunchtime workshops.

That same year, our teaching fellows went to Agadir, Morocco in partnership with the US Embassy — Rabat and AIT — Agadir. We tailored our curriculum again and learned more about building out long-term student communities. For example, we introduced interactive student-centric techniques that reinforced the behavior of asking questions.

We held regular office hours where students were encouraged to explain concepts in their own language and with their own examples to their peers. These students eventually developed workshops of their own to share with their communities.

In 2019, we stayed in the San Francisco Bay Area to focus on curriculum building. We open-sourced all of our code and slides and began developing a guide to incorporate active learning into teaching practices. 80 beta testers reviewed our course.

In the meantime, Loreto Sánchez, one of the organizers and instructors for Saturdays AI in Santiago, Chile, reached out. She wanted to know if she could translate the Delta Analytics curriculum from English to Spanish, and use it for Saturdays AI Santiago’s student course. We were grateful for the opportunity to collaborate with and support Loreto. The experience made us rethink our requirement that Delta teaching fellows must reside in the Bay Area: What if we helped support community leaders all over the world?

For the 6 years since Delta Analytics was founded and the 3 years since the Teaching Fellows program has existed, we have only accepted fellows in the Bay Area. The reason was simple: sustaining volunteer projects over multiple months is hard. For the data fellows, being able to meet in person over the 6-month project is important — these meetings drive community, share skill sets, and creates accountability in the quality of work we deliver.

But for the teaching fellows, this has also created an unavoidable bottleneck. While we have open-sourced both the code and slides for our course, we believe in the power of an in-person classroom for learning new skills.

We think that the scariest part of learning something new is the first few steps when it is easy to drop off due to the flood of information, technical obstacles, and the lack of peers can be overwhelming. Meeting in-person creates feedback loops and social ties that help students overcome the initial hurdle of building a fundamental understanding of the core machine learning fields.

However, creating these classrooms was limited by the ability of our Bay Area fellows to relocate for a few months to a different part of the world. This was clearly an unnecessary blocker for the types of gatherings we hope to support.

That is where you come in. If you made it this far, you likely care about teaching machine learning; you are intrigued by the lessons we have learned, or you may just be a supporter of our mission to bridge the technical skill gap.

We have decided to take our Delta teaching fellowship global and we need your help to find 10 global teaching fellows in 2020. The teaching fellows program will no longer be limited to the Bay Area. We plan to support individuals with a passion for machine learning who would like to grow as an educator and can benefit from our support.

When we say global, we mean it. We are open to supporting individuals in Australia, Europe, Asia, Africa, Americas (North + South), you name the location, and we will try to meet you there with what you need to make it happen.

What does support look like? We will be providing small stipends for classroom setup (such as food for the meetup, any costs needed to set up a projector, internet, and transportation), an adaptable curriculum to suit your classroom, and a built-in learners and teachers community for support. We are, and plan to, continue to be entirely volunteer-driven, so the global teaching fellows will not be a paid position.

We are not sure how this experiment will go. But part of starting small is figuring out where we can make a difference and what type of support educators around the world need. It is also driven by our original goal to let this curriculum evolve with you.

So, apply here or direct someone passionate about bridging the technical gap our way. We are excited to see what communities can benefit through this opportunity!

In the meantime, follow along on our adventure by donating to Delta Analytics, following us on Twitter, LinkedIn, or subscribing to our mailing list here.

Authors: Sara Hooker, Amanda Su, Melissa Fabros, Raul Maldonado, Alicia Tsai, and Andy Kim