Great question, Ankit. I actually took the Data Analyst Nanodegree (DAND) myself and loved it, as did others.
A huge reason why I took the DAND was because I needed help finding a path. If I had access to all of these guides that I’m writing now back when I started, I would strongly consider the separate-course-for-each-subject route since the most of the individual courses within the DAND aren’t the best-rated courses for their subject area.
That said, Udacity’s specialized forums (where paid mentors respond to your questions within hours) and project review process are so effective for learning that I would probably take it regardless. It’d be a bit of an effort logistically, but the most effective approach might be to take the best individual courses for each subject (i.e. the ones recommended in these articles) then enroll in the DAND to complete their projects (there are seven of them) and receive their mentorship.
It’s also important to note that 1) the DAND costs $100–200/month and 2) it only comprises about 50% of my data science curriculum. The other 50% supplements areas where it only offered an introduction and fills in some gaps. This would have been true for the majority of these packaged data science programs.
I do not recommend the Johns Hopkins University Data Science Specialization because the individual courses within it get such poor reviews (examples: Regression Models, The Data Scientist’s Toolbox, R Programming, Statistical Inference).