Data scientists are known for creating their own bubble within the 3I structure -- Implement, Integrate, and Innovate. I personally lean towards the last two Is: Integrate new technologies for constant experimentation and Innovate to attain remarkable results. I have been working with Jupyter Notebook for the last 4–5 years and I feel very comfortable working with it. On the other hand, I share a lot of work projects with my teammate Paolo, who is an expert in building KNIME workflows. You'd think this could be a problem … it's not!

One of the biggest challenges for beginners in machine learning / data science is that there is too much to learn simultaneously. Especially so, if you do not know how to code. You need to quickly get used to Linear Algebra, Statistics, other mathematical concepts and learn how to code them! It might end up being a bit overwhelming for the new users. If you have no background in coding and find it difficult to cope with, you can start learning data science with a tool which is GUI driven.