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Data Scientist Career Track with Python

The 30th of December I finished the “Data Scientist Career Track with Python” on DataCamp.com.

It was a great journey and it lasted 226 h (tracked with the Pomodoro Technique).

I was too lazy to remove the word "Working"

The Career Track is composed of 20 courses, I also enrolled other two, the first on SQL, the second on PostgreSQL

This career track cost 180$, actually with 180$ I have one year access to all the courses, so I can enroll new courses (and after February I will do it) until August 2019.

It was very interesting and I discovered a new discipline that really engaged me.

What I really liked about the Career Track it was the courses modularity, moreover, every 5 minutes of theory, explained through a video, followed at least three exercises.

A preliminary knowledge about Python was not necessary, although I had some basic about C thanks to Arduino.

Will I recommend it?

Yes, if you are interested about the subject, but after the Career Track, you must start some meaty project to put into practice what you learned and avoid the risk to forget what you have learned.

If there is a negative side to this “Career Track”, it is the time needed. On the website, I read that all the Career Track last 67h, I don’t know how they calculated this time.
On average 3,35 hours for a course but based on my personal experience I think the evaluation is not true.

Efforts and time needed to master the subjects explained are higher.
Now It’s time to put into practice all the things I have learned!

On January I have to study for the National Engineer Exam, work on some projects and create a personal portfolio on Git Hub .

I have also promised to Diego that I will write some posts on his blog where I will explain the statistic concept of “Test hypothesis” and errors related to these tests.

Also because as you can see from the first and the following graph, all the time dedicated during these months on Python was for the study on Datacamp (226h of 290h tot.)

Happy new year! 🙂

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