When Carlos Cutillas de Frutos graduated from the Business Administration program at CUNEF in Madrid, he knew he wanted to add something extra to his business skill set. He quickly settled on data science, because he enjoyed statistics and he knew there was a lot of potential for growth there. But he still had a big problem: he had virtually no experience with programming.
After trying a few other options and not finding the success he was looking for. Carlos enrolled in Belgrave Valley. Belgrave, a London-based data science bootcamp program, offers career counseling, networking, and programming training that puts students through our Data Analyst in Python learning path. Starting from the very beginning, Carlos spent his days working through missions on our site, and slowly getting a handle on how to work effectively as a Python data analyst.
He particularly enjoyed our guided projects. “They are the most real thing,” he said, comparing his Dataquest learning experience to his new job working as a Business Intelligence Analyst for Vinterior in London. But it’s not just the guided projects he benefited from. It’s all relevant, he said of his studies: “All the topics Dataquest shows you, you then use.”
So how’d he get that new job in data analysis? He built a portfolio of cool projects and then started putting in the work: applying, applying, and more applying. In total, Carlos said he probably applied to around 60 companies, and most of them rejected him. But he got two offers, and the rest is history.
These days, Carlos says he spends his working hours using SQL to get data from Postgres, and then crunching the numbers in Python using the skills he learned with Dataquest and Belgrave, including a fair amount linear regression. And told us he’s finding his new job really rewarding. “Things that the company didn’t know, you do something with the data and then you’re able to tell them something new that isn’t obvious,” he said.
Want to achieve the same results as Carlos? “Be completely focused,” Carlos says. “You cannot do it here and there, you have to commit.”
Feeling inspired? Dive in and start (or continue) your own data science journey.