Hi, my name is Nieves. I’m a computer engineer and I want to take the next step in my professional journey. So, I decided to participate in IE’s Data Science bootcamp. I’m about halfway through, and the days are packed full of learning and practical experiences that I know will be extremely useful in the years to come.

I’m grateful to have this amazing opportunity where I’ve been able to meet classmates from a variety of backgrounds. Even though we have different personalities, we share a common goal to learn about data science and take on the future.

What is exponential learning? I’m not sure if there’s a definition. What I do know, is that I’m gaining practical knowledge on a wide range of topics. We’ve already dived into the programing languages R and Python, and spent some time on the theory behind statistics and other mathematical concepts. This week, we started on machine learning and all of us are excited about the power of these tools. I feel like I’m a magician extracting the information I need from data.

But before performing the magic trick, you have organize yourself by collecting, understanding and cleaning the data. We are learning how to automate this process, but it’s difficult because our teacher challenges us by using imperfect data in every exercise. After all, that’s what you get in real life, so I’m sure we’re learning a lot.

Alongside our classes, we work in groups on the capstone project and arrange weekly client meetings to ask questions, reach agreements, show our progress, etc. This week, we were lucky to meet our client in person. It’s not a requirement, but putting a face to the name makes us feel more connected and helps us communicate better. In our case, the client prefers to explain some technical processes in Spanish, so we’re always having to translate. Sometimes, it feels like the Tower of Babel.

There are many things you have to think about when working with data. Although we haven’t come across it yet in class, we have to deal with geospatial information as well as loads of other research. And that’s not even counting the enormous amounts of information the client provides us with. We have to pick only what we need. Otherwise, we wouldn’t be able to finish on time if we processed all of that information. Now, we’re thinking about how to model data and it’s a big challenge to choose a solution that everyone in our group agrees on. These are situations we’re going to face in everyday life.

It’s not all work though. We also have time to socialize during our coffee break and lunch time. The Resilience class is also a great way to help us relax and not burn out from going so fast. Every week, we apply what we learn in that class to our lives. For example, you can’t always control what happens, but you can choose how you handle the situation. As well as this, we’ve begun to take yoga classes. I’d never done yoga before, but I usually think experiencing something is the best way to decide if you like it. I find I never regret the ache in my body afterwards because I always sleep like a baby.

Interested in learning more about our Data Science Bootcamps? Click here!