It is that time of the year again; the time to introspect on the year that went by and to make plans for the new one just around the corner.
I have had a lot of folks reaching me over the past few months, seeking advice regarding a career switch to Data Science and ML. I wanted to take this opportunity to pen down my thoughts on this topic, so as to be able help those wanting to make this transition.
Before I proceed, I want to clarify what the terms Data Science and Machine Learningmean. Firstly, they are not synonyms – they mean entirely different things. Hence the skills required are different too, albeit there might be some overlap.
Data Science is the art & science of gaining insights from data, and presenting them in a business-friendly manner.
Machine Learning is the set of tools and techniques that can be used to automate a “decision making” process. It maybe useful as a part of a Data Science initiative, but is definitely not a necessary toolset in the Data Science initiative.
I will try and describe the various roles that are usually part of a Data Science initiative and the skills required thereof.
The point to note, of course, is that more than 70% of the effort in any Data Science initiative will be on the data engineering side. Hence, most of the jobs will be in this space too. It is absolutely imperative to brush up Undergrad stats and maths, as you plan to get into this exciting field of turning data into stories.
Here is to a geeky 2020, guys…Have fun and be safe.