Data Science

Hi all,

One thing that I am doing for professional development this summer is to learn about data science. With help from a friend, I decided that DataQuest’s Data Science in Python course was the best option for me. I looooooooove Python, so it was an easy choice to choose Python over R. (Note: DataQuest has not asked me to write this post, and I am not getting paid to do so—in fact, I am about to give DataQuest money to unlock more assignments. Thus, these opinions are truly my own).

I decided on DataQuest over its competitors because of its lack of videos. Each assignment is basically a page of text describing the theory on the left side of the page, as well as a list of tasks to do (also on the left side of the page). There is either a terminal or a Jupyter Notebook on the right side of the page, and this is where you do the tasks.

The lack of videos allows me to work at my own pace. I have some experience with Python, so I sometimes just skip the reading and work on the tasks. Watching videos would drive me crazy, I think, as it is impossible to just scan for the items that you don’t understand. If I feel like I ever need a video explanation on a topic, I am guessing that I can find a free video online that explains it.

I am about 8.5 hours into it, according to DataQuest’s timer (although I think that I might actually be closer to 6.5 hours into—I think that I was AFK for some of it with the clock running. I am 11% complete with the entire course. So far, I have only been learning about things that I mostly already know (the Python language, although I have definitely still learned a good amount of new stuff about Python), so I don’t think that we can project my finishing time from what I have already done.

I probably have about 2 hours more of free material. After that, I am planning on paying for the premium plan, which is on sale for $25 per month (it is normally $50). I am hoping that I can finish the Data Science with Python program within two months, so I don’t think it should cost that much money.

I am really enjoying it. It is nicely challenging—enough so that you learn, but not so much that you get frustrated. I am also teaching probability and statistics next year, and I am going to be using some of what I am learning in that class.

4 Responses to “Data Science”

  1. Joss Ives Says:

    It’s funny how many of us are learning how to speak (and do) data science. I have mostly been working in R because that is what the local expertise uses. I hope you have tons of fun!

    Are there specific projects that you have in mind once you are done?

    • bretbenesh Says:

      Dear Joss,

      It is cool that you are learning it, too! I am fortunate in that (1) I love Python AND (2) it is what our school (essentially the CS department) decided to use.

      I don’t have any projects in mind. This is really just for me to learn what Data Science is, which seems like something I should know. How about you?

      • Joss Ives Says:

        A lot of the education research that I’m involved with pushes in the direction of data science, especially the stuff that uses log files from PhET simulations to try to understand what students are up to.

      • bretbenesh Says:

        That sounds like it would be really useful for you to know! I decided to stop with the free material. I have a good sense of what data science is now, and every hour I do that takes away an hour of research. So I decided I have to prioritize.

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