Is coursera specialization of data science or big data enough to join the market as data...

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Abdelbarre Chafik


Thank you Mahmoud Metnawy for A2A

Yes of course, when you get certified and especially from self-learning courses you will have a good chance to get job because it show that you really have motivation and you like the fields of Big data and data science, and this a good point in your resume.

Image Ref : Course Certificate | Coursera

Coursera is one of multi-platforms of self learning, and it is one of the best. I advise you to take big data courses in this platform and get certified by one of the big universities that propose the courses But as Schmichael Chen said to in on comment “Learning never stops in life” I wish you can add more courses and certifications and in this time your percentage to find a job will increase of course, also try to find a project in Your Home for Data Science (very useful to learn by practicing).

Some of courses/books :

• Big Data University | Data Science Courses (Free and excellent Courses+ certification IBM colaboration )
• Learning Data Mining with R [Video] (packetpub video course)
• Introduction to Data Science | Lynda.com (paid)
• Data Science | Udacity (paid+ certification)
• Learning R for Data Visualization [Video] (Packtpub video course paid)
• for more courses: Abdelbarre Chafik's answer to Can we become data scientist by going through online tutorials?
• Learning Data Mining with R (book)
• Hadoop, the Definitive Guide By Tom White (book) http://www.amazon.com/Hadoop-Def...
• Practical Data Science with R By Nina Zumel and John Mounthttps://www.manning.com/books/pr...

Hope that Helps You

“Learning never stops in life”



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Ricardo Vladimiro


I’ve answered many of these questions in the past and it seems that most answers assume that the MOOC and the job market are the only variables to consider. They aren’t. They are not even the most relevant. Answering yes or no to this question is an exercise of how biased you are. Yes or no are not valid answers.

These (and other) MOOCs are sufficient depending on your ability to perform, the role you are applying to, who you are competing against and the hiring manager. With that in mind let me give you the perspective of a hiring manager:

• The single most important thing that a hiring manager is looking for in someone applying to a position in his/her team is the ability to perform the tasks in the job description. That is achieved by sending a test task to the people applying to the job. If the MOOCs give you that ability, you will proceed to the next stage. If they don’t you and you don’t have the knowledge you are out.
• The second part is the role you are applying to. Let’s say you have data analysis experience and you took these courses to augment your knowledge. You are likely to be considered to receive the test task for a junior or mid position. You will not be considered for a senior position, I’m afraid because you’d need to have the experience before taking the MOOCs.
• Third part is who you are competing against. Let’s say that you have no experience in a data related job and you did these MOOCs. If someone hires you for a mid/senior position, then they have no idea what they are hiring for. However it is possible to apply for a junior position. In this case you’ll be facing people fresh out of college some of them immensely talented. Is it possible to beat them? Yes. Is it easy? Hell, no!
• Last but not least is the hiring manager himself. Some of them don’t know what MOOCs are. For them you are in bad shape. Some of them know what MOOCs are and don’t like them. You are also in bad shape. Some of them feel that people that do MOOCs are interested in continuous development. This is my case. I believe MOOCs are very important for continuous learning.

Depending on how you fit in these 4 points, you may or may not get a data science job. Keep in mind that this is a very complex question and that those 4 points are simplified views on the things that matter when hiring someone. For instance I’m not including non technical parts, like team fit which is very important but outside the scope of this answer.



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