How Predictive Models Can Guide the Way to Student Success
Why Have Side Projects? Whenever I am asked the best ways to learn data science, I always encourage folks to find a problem to solve that is interesting and unrelated to work. In other words, a side project.
The rationale for this advice is simple: learning new tech skills is difficult. Therefore, you should tackle problems that bring as much joy as possible while also avoiding email entanglements or late-night Slack boondoggles.
How are you using data to leverage more growth in your institution…and how can you do it better?
Multi-arm bandits and content optimization
I have enjoyed NPR’s Planet Money podcast for many years. They always have an interesting perspective on matters foreign and domestic; macro and micro; trivial and critical. It’s also a space that doesn’t shy away from wonky, data-filled policy debates.
A recent episode, The Modal American, talked listeners through a full analytic pipeline including the research question, an explanation of the methodology and the results.
Planet Money’s specific research question was whether they could aggregate IPUMS data (Go Gophers!
Welcome. I’m so glad you could make it.
If I had a dollar for every person whose told me I should start a blog, I wouldn’t have very much money. For the sake of conversation, let’s call that value zero.
Just because there’s a lack of overt market demand, I went ahead anyway. Here’s why:
The intersection of higher education and data science is still relatively underexplored. Colleges and universities have a multi-generational responsibility to society and should be held in the public trust.
How Advanced Analytics Can Create a Win-Win for Students and Institutions