Time truly flies when you’re learning data science! I wish I could say that is always synonymous with having fun, but the bootcamp has proven quite challenging at times. Either way, six weeks are in the books, and we’ve already reached the halfway point in the course. We’ve really started to hit a stride with the amount of material we’re covering on a daily basis, and actually absorbing the lectures has seemed easier as time has gone on. With that being said, our last assignment, Project McNulty, was a step up in terms of difficulty compared to the previous two projects. Not only were we required to build a classification model of our choosing, but we had to turn it into a web app and incorporate an interactive visualization as well. Luckily this one was a group project, so there were four of us to distribute the workload between. After much deliberation, we decided to address a classification problem surrounding Lending Club loan application data. Namely, we set out to predict if someone, given their credit history and demographic information, would be accepted for a loan. If they were to be accepted, we also wanted to predict the grade of loan they should expect to receive. As peer to peer lending has become a useful instrument for many in securing financing, we thought it would be both interesting and helpful for potential applicants to see if they should expect to be accepted for their ideal loan.

It’s been an arduous, if not exciting last three weeks of bootcamp work. Between exercises, projects, networking and trying to absorb all of the material, the course has shaped up to be a real juggling act of effort and time management. While the entire experience has proved enlightening thus far, the whole reason for signing up for the bootcamp was to gain tangible, applicable skills in data science. I certainly haven’t been disappointed yet, and the fundamentals of data science that we’ve been learning were showcased first hand in our most recent assignment: Project Luther.

The first week of the boot camp is in the books, and it’s off to a scorching start. While the pacing was somewhat of an adjustment to get used to, after finishing a years-worth of intense study for my master’s degree it felt a little like riding a bike. The first day was complete with introductions, administrative duties, and even a preliminary lecture on Pandas. While the lecture was effective and broad, it was different than a traditional academic course. Specifically, I really enjoyed how applied and practical the instruction was, and this aspect of the boot camp is exactly what I signed up for.