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Less than a month left of the #DataCamp subscription. I need to look at the "professional" tracks and pick something that I can accomplish in that time.
Lots not to like ... in many ways, their courses and especially their practice exercises look like they hired a couple of college kids to build them over a weekend, then posted them without having an editor look them over.
In multiple courses under the subjects of Python, SQL, Julia, and R-Lang, the exercises will mis-spell a language keyword or some library function / method that is widely used in Data Science. In a couple, the answer is already entered into the question ... just select the choice that matches what they've just showed.
In the "real world" projects, they tend to go beyond what the courses have covered. Yet, they're opinionated about which functions / methods are used (and sometimes even the order they're used in). So you do some research, find some functions that produce the exact desired results, and the project is rejected because your research didn't uncover the desired functions to use.
Now, there's lots to like, too. For example, despite having both R-lang and Julia (and Scala) on my to-learn list for years, this was my first hands-on experience with all three.
- clacke likes this.
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Also, I appreciate having their built in interpreter, because it frees me from having to install everything the courses cover.