Could you introduce yourself? What were you doing before you joined Constructor Learning’s Data Science Bootcamp?
“Hi, my name is Adrian. I'm currently a Data Science and Natural Language Processing Engineer at Advisor, a small startup here in Zurich, Switzerland. Before joining Constructor Learning, I worked at a self-driving car company in Silicon Valley, but I wanted to be closer to actual Data Science and closer to programming, and I wanted to live and work in Switzerland. I have chosen the Data Science bootcamp at Constructor Learning because it was the easiest way to network here in Switzerland.”
Why did you want to get into Data Science?
“I wanted to get into Data Science for a couple of reasons. Firstly, it is a field with a lot of potential for career progression. Data Science is a highly technical and quantitative field and that really lined up with my interest in my previous accomplishments. The second reason is that it is a way to quickly provide value to a company, especially if the company is looking to accelerate their growth and they have a lot of data. They need somebody who can understand that data and be able to visualize it.”
What were your highlights during the bootcamp?
“I really enjoyed working with my teammates, especially because we could all learn from each other. We all came from diverse backgrounds. We had an Accountant, a Flood Risk Analyst, a Hydrologist, etc. Another thing I liked, in particular, was how the Bootcamp provided us with projects from companies in Switzerland who needed some sort of technical help where we could turn around and take what we learned and apply it very quickly. For instance, Merkoi, the company that I partnered up with to help them develop a new system for classifieds in their tests. That was immediate and it was a great way to build some experience.”
What was your Capstone project about and which technologies did you use?
“The Capstone project I was on was with a company called Merakoi. They are a company looking to provide pharmaceutical companies with more information about the patient experience. Me and my teammates were given a large data set of social media content related to Multiple Sclerosis. Multiple Sclerosis is a very difficult disease to treat and the people who live with it have many different kinds of complications. You get all these different kinds of symptoms and certain treatments apply to certain people some way and to other people in another way. What Merakoi was trying to do was to pull all of that data together and see if there was a way to aggregate that data. We applied Natural Language Processing in order to classify and group the data into different types of responses that people were saying.”
How to start with Deep Learning?
“The best way to start with Deep Learning is to build a base of programming in general, understand how programming works, how Machine Learning works etc. From there I would say look to step up into the next step of understanding how all the pieces of a Deep Learning model operate with each other and I think it's easiest to take classes or to collaborate with other people.”
Was it easy to find a job after the bootcamp?
“I did Constructor Learning partially because they were able to help me break into the startup scene in Switzerland, and they did an excellent job! At the final project presentation event somebody came up to me and talked to me about my Capstone project. He really liked what we did and invited me to an interview. I'm still working there today and I'm really happy with my decision overall that I did Constructor Learning's Bootcamp.”
Thank you, Adrian. We wish you all the best!
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