Machine learning, artificial intelligence, deep learning, and data science are four terms that I believe are going to change the way we have always looked at things. Let's see if I can convince you why I believe so.

From making a computer learn how to play Go and defeat the world champion of the very same game to using the same branch to detect whether a person has a tumor or not just by seeing their brain's CT Scan, machine learning has left its mark in every single domain. One of the projects that I worked on was using machine learning to determine the residual life cycle of boiler water wall tubes in thermal power plants. The proposed solution was successful in saving a huge amount of money by using the tubes more efficiently. If you thought that machine learning applications are limited to engineering and medical science, then you are wrong. Researchers have applied machine learning concepts to process newspapers and predict the effect of news on the chances of a particular candidate winning the US presidential elections. 

Deep learning and computer vision concepts have been applied to colorize black and white movies (have a look at this blog post—https://www.learnopencv.com/convolutional-neural-network-based-image-colorization-using-opencv/), to create super-slow-motion movies, to restore torn out portions of famous artworks, and more.

I hope I have managed to convince you about the importance and the power of machine learning. You have made the right decision to explore this field. But, if you are not a computer science engineer and are worried that you might end up working in a domain that is not your favorite, do not worry. Machine learning is an extra skillset that you can always apply to a problem of your choice.