I recently got accepted into the University of Denver Masters in Data Science Program. I start next Fall and I am wondering how well do you think using Dataquest will prepare me for a rigorous curriculum? I figure I have 9 months to try and get through the whole data science path in Dataquest, but in reality I feel like in order to really be good and understand what I am doing would take closer to two years. I do feel confident I can be quite knowledgeable in the concepts towards the beginning of the data science path but find I may simply be skimming through the latter parts of the Dataquest curriculum in attempts to prepare me as much as possible.
Considering I am going for a masters, should I be overly concerned about going into depth in each of the missions, or should I simply run through the entire curriculum a few times in hopes that I will have a broader knowledge base going into my degree program? I only ask this because I am coming from a non-computer science background.
I never had a masters, much less data science masters, but i have seen DS masters exam papers from my friend. Also, i have seen undergrad machine learning courses in my own university and both are surprisingly theoretical. Therefore, if i were to take masters, i would focus on practical software engineering skills first, fast implementations, quick experimentation, so you can take the theory and do multiple simulations quickly to get some empirical results which could help you with theoretical proofs. You can indulge in theory when your masters comes, and you have professors around to give you quick answers, which to me is a more efficient way of learning than you going hardcore on theory now without readily available support. Don’t spend 9 months all on Dataquest, because while it is a good starting point for concepts, it could get you accustomed to have an instruction screen which is but 1 style of learning (slightly slow in retrospect for me now). Finding relevant pydata videos on youtube could give you leaps in understanding a topic, because those presenting usually share the industry standard techniques and some bring decades of experience.
For an introduction to any topic on data science, the concise articles on
have been very helpful at the start of my journey , and the knowledge there i still use 2 years later in my interviews now. For python examples, realpython.com articles are really comprehensive and get me up to speed within half a day.
First, best of luck for your data science program! And, I think DQ will help you! Just contact him through support center!