Training Debt

This morning, I was listening to a wonderful discussion on technical debt as it relates to machine learning, and I began thinking about the technical debt we’re carrying with our classes. Next week it will be 5 years since I taught the first iteration of what would become our Data Analytics for Managers class.

In that time, I’ve learned a lot about how to teach data analytics skills and techniques, not to mention the very important data-driven mindset that is at the heart of all our work. I’ve had a lot of help from co-instructors, consultants, and mentors along the way to come up with some key design patterns described in a recently published post, but it’s important to acknowledge that each class, like an application, has a history, a context, and constantly unfolding present.

As I bring on more collaborators, I’m having to make explicit what I’ve carried in my own head, articulating intention and purpose so others can carry forward the experience. This leads naturally to conversations about whether this is in line with our intention and values. I also believe our participants benefit from a more intentional approach we can easily explain to ourselves and to them.

Our debt now is in how we evolve each of our training experiences to more fully implement the experiences we’ve had, implement the lessons we’ve learned, and make the classes better for participants. We’re still getting good reviews and feedback, so it’s not that anything is broken, only that it could be better and more consistent with our core values. As someone who is constantly optimizing, I have to remind myself the issues I see plainly may not be obvious or even apparent to anyone else.

So expect to see changes as we constantly improve the classes we offer, paying down our debt to better implement the values and patterns we’ve found valuable, improving the experience for participants, and allowing the unique experience of each of our team members to come through in the learning experiences we offer.



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