After spending almost 10 years in analytics-related jobs across several industries in various countries, for a while I’ve been hesitant to take the next big learning step and finally understand what these buzzwords—“data science,” “machine learning,” “artificial intelligence” and so on—are all about.

Having already completed two master’s degrees, I didn’t want to invest in another long-term academic endeavor without being confident that it is really the right call. IE University’s full-time Data Science Bootcamp is only three months long, which felt just like the right amount of time and effort for getting my head around the essence of the discipline and, hopefully, for understanding what to do next with my career. So, here I am now living in Madrid and studying data science and machine learning at IE University. Exciting! And a bit scary…

To be honest, the first two weeks were not as intense as I was told they would be before the start of the program. I’d say that if you already have some sort of programming background, even at the very basic level, you’d feel pretty comfortable at the start of the program, if not to say that the first days may feel slow. However, I recognize that those of my peers who had never been exposed to coding before needed to process loads of information in a short period of time—a challenging task indeed!

It is also evident that the intensity is increasing along the way. I’m sure the moment where I’ll kick myself for saying “the program felt slow at first” is just around the corner. In fact, my intuition and common sense are already telling me to go and start reading the math and stats materials right now! I admit that the “going slow to go fast” approach adopted by the IE Data Science Bootcamp makes total sense. The material is well-structured and delivered in a way that is easy to digest for anyone, independently of their previous background. The Bootcamp looks to be a “kind” learning environment where everyone wants you to succeed—just as long as you are willing to learn.

Looking at the Bootcamp’s detailed calendar, I find the structure of the program to be reasonably balanced. What’s more, I’m positively surprised to find a pair of “soft” subjects in the program syllabus that I didn’t expect to see among mathematics, statistics, Python, and machine learning modules: “Leading Global Agile Teams” and “Resilience.” Coming from a business background, I have no doubt that the key to success often lies in a combination of “hard” and “soft” competencies. There are definitely times when you need to manage others (for which agile project management methodology might be helpful) and there are times when you need to manage your own thoughts and emotions, keeping calm and breathing deeply.

Personally, I am very impressed with the backgrounds of the teaching staff at the IE Data Science Bootcamp. The majority of instructors are well-rounded both in academia and in practice. The CVs of faculty members are gleaming with PhDs, names of top consulting firms, or well-known scientific institutions. You can find CEOs, company founders, or heads of business intelligence departments—top-performing roles in top-performing organizations. These are just the people you’d want to learn from, as well as the very people you’d want to have a beer with after class to ask them a ton of questions.

I’m finishing up this diary entry on a note of excitement and curiosity about the next 10 weeks, and so far with a good feeling that I made the right decision by joining the IE Data Science Bootcamp. At least I hope so, but just in case, I’ll get started with those maths and stats materials right now!