Everything began in April. I came back to Spain from Mexico City after having visited some friends, and I decided to start an active job search. I still remember that some friends, in different contexts, told me:
Gosh, it seems that you will end up prostituting yourself to obtain some CV experience.
But, that didn’t happen.
As a matter of fact, I spent 3 months (since early April until late June) looking for a job, and I finally didn’t work at anything at all. Why? Basically, because of the following:
- Conflicts between institutions at my university. Even having talked about a contract, everything we negotiated was ignored, as well as my CV.
- The descriptions about the interns given at my university were really sparing, and they didn’t match with the interests of the contracting parties.
- Time. I received several calls to work in a business in Madrid, but I couldn’t spend 6 months working far from my university, as well as studying.
This doesn’t mean I didn’t have job opportunities available; in fact, I could have chosen to work in an administration task or in a McJob. However, I thought there would be some other alternatives for someone that has a slightly technical profile such as mine, so I decided to ask for advice to some lecturers of my university about different options.
In this double degree that I’m studying, as well as reading some related piece of news, I have realized that topics like the Artificial Intelligence might have some impact in the future. And not only in the technical scope, but also in the economical and the social ambits. Therefore, I have seen that areas like the Data Science might have some interest regarding to the future (but it might get obsolete soon too, who knows 🙁 ). That’s what dragged me to take some courses in Coursera about this particular topic.
The following question will certainly be:
What is Coursera?
Coursera is a MOOC (Massive Open Online Course) created by Daphne Koller and Andrew Ng, professors at the Stanford University, with a clear aim:
Give everyone that has access to the Internet a quality education.
It’s all about free courses, but in some cases you have to do some payments if you want to obtain certificates to get credit of the acquired knowledge. This institution has agreements with various universities which offer online courses with some specific deadlines, as if they were university courses.
However, someone could easily doubt about the capacity of these courses, as there might not be such an extensive evaluation as in face-to-face classes. But, obviously, that’s the own student’s issue; i.e., these courses offer various evaluation methods like automatically graded tests or peer-graded tasks. If they are done seriously, they can assess your knowledge of the subject, as well as give some interesting feedback to learn further.
But, clearly, this model begins with a basic assumption:
The person enrolled in the course wishes to learn and is ready to make an effort.
I accomplished that objective in my particular case, because I was quite confused during the last summer about what to do. I knew I wanted to do something, but considering all the problems I had to get a job that could give me some useful background, I made up my mind and began with these courses; specifically, with the ones that were part of the Data Science Specialization, offered by the Johns Hopkins University.
Thanks to this ‘specialization’ (even if I haven’t completed it totally), I can assert that it answered me some questions about the Data Science, like:
What’s that? What’s it used for? How do people work in this field?
In fact, now I have even more questions than I had when I started, but I know they are more precise, and I guess I could answer them with a deeper study of the subject. It’s a field much broader than what is mentioned at this specialization, but I think it has given me a better perspective to understand it properly.
So… A reader might wonder the following:
Let’s see. I take a course, investing time, effort (and money) on it. However, I know these courses don’t deepen so much as an university degree. Which is their use, then?
I feel that any student taking these courses must set clear expectations before beginning with them. These courses won’t arrange your life; I mean, doing a Coursera course won’t make you the ideal candidate everywhere.
Even though, if you are a person willing to learn, and that wishes to learn about:
- Topics that are a bit far from your main knowledge field.
- Topics which you cannot learn about because there aren’t educational centres near you that teach about them.
- Topics on which you have preliminary concepts, but you would like to have a solid basis on.
Coursera might suit you. There are various offers from a wide array of topics, starting from the STEM (Science, Technology, Engineering, Maths) to social topics. Even if they aren’t something that will guarantee you to be a big fish, they can become an interesting asset (if they are related to the field you want to work at) to demonstrate your interest in a specific technical area.
At any rate, even if this is a short testimony of mine, I guess nobody can describe how Coursera works, its objectives and its prospects better than Daphne Koller, the co-founder of Coursera, at this TEDXTalk:
[Originally written at August 23rd, 2016]
