What is the difference between Columbia's MS in Data Science and Columbia's MS in CS with the machine learning track?

First of all, Columbia's MS in Data Science and Computer Science are both excellent programs. But I do want to suggest you know it with some elements. You see, even with MS computer science with the machine learning track, it offers way too many options. So, you can choose from numerous courses under the MS computer science with machine learning. Whereas MS in data science is more of statistics and analytics. In a way you kind of stick with it, which by the way is not a bad thing.

This option delivers to more individuals who are interested in the field. You may not know how many students change their career paths while in their masters. In this case MS in CS with a machine learning track is far more viable.

Now, this may seem a bit technical, but important if you want to figure out the difference. The MS in data science does consist of computer systems and operations, machine learning etc. But it's far more directional. The course options for MS in data science will be more focused on data science principles. Of-course it goes for MS CS with machine learning as well. However, MS CS machine learning track will offer a wider CS learning.

As complicated as it seems, it's just a matter of limit on availability in both programs. You can either go for a rather more universal opinion or a directional one. Simple right? And if your career modules are already set, just go for the required elective options keeping the subject approach in mind.