As week four comes to a close, we’re well into the Data Science Bootcamp. It’s finally time to start analyzing datasets from real-world companies and put our Python coding skills and statistical methodology into practice.

In preparation for our presentations at the end of the Bootcamp, we kicked off this week with our first data lab. We split into teams and started to explore the data we were given. For most of the Bootcamp, we’ll be collaborating with the client and preparing the data, but we’re all itching to get to the fun part—data modeling.

I’m eternally grateful for working with such a diverse group of students, both in terms of nationality and age. There’s also a great mix of men and women in the group. IE’s recruitment team did a wonderful job with promoting diversity into this male-dominated field. It’s been fantastic getting to know my peers professionally, academically and personally.

We recently had our first house party, courtesy of two generous bootcampers who moved to Madrid for the program. We had such a great time that I may host the next get-together.

So far, my main takeaway from the Bootcamp has been an in-depth understanding of data science. It’s so much more than a Kaggle competition. From start to finish, collecting, analyzing and interpreting data to help drive a company’s performance is a complex, time-consuming process. But after IE’s Data Science Bootcamp, you’ll be one step ahead of the rest.