Data Scientist at Owlytics
Data Engineer at AllCloud
In a young startup like the one I own, we are doing a bit of everything, from big data to DevOps to data science. As we grow bigger, algorithms get more complicated. I joined Y-DATA to understand my data team better. Now I can understand their work better, know how they're approaching the problem. It helps us move along much faster and bridges the gap between management, engineering and data science teams.
I realized that as a product manager in a travel tech startup, I needed heavy tools to analyse data, do predictions and more. So I started checking all kind of data science boot camps, machine learning academies, but unlike most of them, Y-DATA looked realistic. I chose Y-DATA because one year is better in terms of understanding things. Also I could combine it with my previous work.
I think the very best thing about the course are the people. The selection of the students for the course was really good. Heterogeneous people from all kinds of fields and different backgrounds - that’s really good. We had some projects together, worked as groups, that was a good way to get to know other people. We were all sitting in the classroom together, talking and trying to figure out how to do the homework later on. It's great.
Fraud Detection Lead at DoubleVerify
Deep Learning researcher at Trigo
Software Engineer and Data Scientist at Fiverr
Data Scientist at KHealth
Great experience so far! Personally for me, the course exceeded my expectations. I usually stay away from courses since I'm a self learner. Courses usually spend too much time on the unimportant parts (too much history, too much theory, repetitive exercises, etc.) However during Y-DATA courses we had exactly the right balance of practice and theory.
You know they say go with your passion, right? I’ve been programming since I was a kid, but I never really dealt with Data Science or Machine Learning before Y-DATA. I already knew the math part of the introductory courses but they were so fast-paced that I wasn't bored and quickly enough we got into supervised learning and deep learning. This gave me the tools to do things that I couldn't have done before, let me explore and widen the area of my thoughts.
It was obvious to me that math is the field for me. I did my B.Sc and M.Sc in math. In the industry, you can do a lot with math, but you must have knowledge in computer science as well. Y-DATA was exactly right for me - it let me combine my background with computer science and strong data science foundations.
I wanted to get into this world of data and data science. I had a feeling that this field is mine. That was my main purpose, to get the most out of this program and out of the industry project. I think our learning group was most important in my experience. It was small but diverse. Everyone is a specialist in something a little bit different so we really helped each other. There are very good students in this program.
For me, the most important aspect of the program is the industry project. There's nothing like working on a real problem with experts in the field. I feel that the classes prepared me well for this kind of hands-on data science work. In particular, the variety of lecturers from tech and academia is definitely an advantage of the program.
I'm an Engineer. I studied math and physics, and financial engineering. I choose Y-DATA because I wanted a better understanding of the algorithms. When you have access to machine learning techniques, you have access to more tools, allowing you to do more things.... For instance, in my field, in time-series analysis, you want to better predict and better focus.
Studying in Y-DATA is like building a muscle. You need to work on a muscle to be a better, stronger person. It's a very good program because it shows many things.
The course is great, I think it’s the best professional course I have taken and for me personally it’s a good substitution to a masters degree (for now). Even though I'm already working as a Data Scientist I still learn new things, there are always fields that I'm less proficient in and the course fills that gap.
I was looking for the best place to get ML background, to learn more techniques, better and wider knowledge, especially in deep learning, which I didn't know anything about. I chose Y-DATA because it was presented as a program that can mediate the gap between academia and industry. This was exactly what I was looking for. I don't have professional experience in ML but Y-DATA gave me a really good background so I can bring a lot to the table in addition to my research background.