I see many ads that claim to make you a data scientist in 12 weeks. They say they can teach you Python programming, python libraries like Pandas, Matplotlib, and scikit-learn, another visualization tool like Tableau, SQL, and probably more. After 12 weeks, you will get a job that will earn you about 100,000 USD. But before that, you have to pay a good amount to take those classes. How realistic they are?

Are They Realistic?

It depends on which level you are in. If you already know a programming language and switch to Python for a new career, then you can learn all this in three months if you work hard. But if you do not have any programming background, then it will be too ambitious to think that you can learn all this in three months even if you do not have another job and you focus only on study.

A Reasonable TimeFrame

If you want to become a data scientist, you need to learn at least one of these two languages. And learning programming languages does not mean just learning if/else statement and loops. It is more than that. You need to learn the data structures and programming problem-solving which takes some time. You should dedicate at least three months to learn a language only. If you do not and rush into learning libraries, databases all at once, you may end up learning everything to an extent that it will not be useful. I am not saying you need to be an absolute expert in programming before you can start learning anything else. But you need to be at least comfortable writing some code solving problems. There are a lot of programming problems out there to test yourself. I suggest, try leetcode. They have three different categories of problems in leetcode, easy, medium, and hard. See if you can solve some easy problems. Then move on to learn the libraries like Numpy, Pandas, Matplotlib, seaborn, scikit-learn, and others.

Learning just a few of those libraries should take another three months. It takes some time to practice and grasp the ideas of Exploratory Data Analysis and do it yourself. Learning SQL should not take too much time because you will find lots of similarities between Pandas and SQL. But still, even if you learn fast, learning to use several big datasets and intermediate level complex queries, organizing and setting up datasets will be a couple of months. So, I am talking about at least eight months.

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