The Data Science Path is repetitive and not well put together

Community Feedback & Requests
1

Hi,

As said in the title, I find the Data Science Path to be a bit repetitive and not very well put together. What I mean is that it’s quite obvious that instead of being one very big course which contains the material of multiple little courses, it’s just a bunch of little courses put together. I understand that it would be virtually impossible to re-do every course so that it fits well, but still.

More precisely, some topics are seen multiple times, some are seen in an order which I find to be strange and as courses are made to be standalone, it’s always made as if it was the only course that you’ve taken.

For example:

  • A topic seen multiple times:
    The use of a histogram and all of the theory about it is explained in part 11., in the course “Introduction to MatPlotLib”, but then it’s also all seen again in part 14., in the course “Histograms”. The latter is a better introduction into it and should be seen before I think and then just the practical aspect of how to plot it should be in the matplotlib course.

  • Topics that are in the wrong order:
    In the matplotlib and seaborn introduction courses, the box and violin plots are seen, and both use statistical quantities such as the mean, the median, etc. These quantities are not at all explained (which is fine, I can search online if I want), but then, there’s complete courses on each of these quantities, but AFTER. I just think that it would be way more logical to explain these quantities first and then see them “in action” in a box or violin plot.

  • Courses meant to be standalone:
    In a lot of courses I have seen half of the explanation being about Pandas, numpy, list comprehensions, etc. when one part of the code used one of these libraries or mechanics. I think that this could be easily fixed if these explanations were in a separate page or “slide” of the course and then ignored if the course on Pandas or numpy, etc. has been seen by the person.

These points are not that big of a deal, but they are little things that annoy me quite a lot, and, frankly, makes me want to stop using codecademy at that time to do something else instead.

2

Hey there,

I’m 75% on cs path and 30% and I feel you on your critiques (I have many too).
I think any resource at this point is going to have its strengths and downsides. Diversifying can help overcome this (books, good youtube channels, irc, discord, other more specific sites for certain topics).

I will say that for all the shortcomings I can often come back to these forums and get some in-depth look at a variety of things (delivered in a civil way, which is not the same everywhere).

I’m sure they are trying to improve on ironing out these kinks, but between that and developing new courses for the ever-changing environment, it’s a balance that would probably require a more expensive subscription model (my opinion here). At a certain point, the cost-benefit is not going to favor codeacademy. There are other institutions that do deliver a fuller training, but the price is accordingly more expensive.

tl;dr: there’s no one stop shop at this price point.

I feel you though, curriculum structure is very dear to my heart (as I am a teacher) and seeing it like this does grate me. But I take what I can from it in spite of the structure. I wouldn’t recommend it for everyone

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Thank you very much for the feedback! I assure you that we are keeping an eye on submissions here even if we don’t always reply and can’t always take action. In this case however we are indeed reinvesting in the data science and web development paths as we speak and this feedback was useful for that. :slight_smile:

Let me lower your expectations though, (re)building content is a very time consuming endeavor so we can’t make all the improvements overnight, but stay tuned.

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Thank you for your work! Great projects take time to build and I truly think CA is trying to put out a great product.

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