"The Analytics Edge " verified track - Worth for switching career into Data Science



Hi all,

Please accept my sincere thanks for creating such a wonderful resource on analytics. I have been following analyticsvidhya for quite sometime now and found it very informative. AV is one of the best credible source in India on Tools, trends , training, guidance on analytics industry.
While learning of analytical tools like SAS, R , Python etc is required to switch into analytics field , MOOC courses from Coursera , edx provide a platform for newbies to get a fair idea of such tools.

Can you guide on verified track / signature track courses from such online platforms. More specifically, how would you rate following three online courses.

1 - Data Science Track from Coursera - Signature Track / free version ( 9 Course track)

2 - Analytics edge from Edx - Verfied Certificate

3 - Data Science + Big data course from Jigsaw Academy


Here is how I would go about it:

  1. Ask yourself, how motivated you are to learn new tools on your own? MOOCs are great to learn new skills in cost effective manner, but need you to be super motivated. The drop out rates are typically very high. So, if you think you can spend time watching videos regularly, solve data science problems on your own (with help from discussion forums) - you should go with one of the MOOCs (go on to next step). If you think, you will need a mentor or an instructor to go to with your doubts - go for the course from Jigsaw.

  2. If you have decided to go down the MOOC way, next you need to decide how much time can you spend every week. The Data Science track from Coursera is relatively light - 3 - 4 hours every week for a period of 9 months. Analytics Edge on the other hand is a very involved course. It will require you to spend 10 - 15 hours on some challenging problems. However, if you persist, it will enable you to compete in Kaggle competitions by end of it. So, if you need lucid introduction to the subject with relatively simpler assignments to start with, go for specialization from Coursera. If you need more serious challenges for your brain in shorter term - go for Analytics Edge from edX.

Hope this helps.




I can understand the confusion you might be facing. I have been there and tried out several courses in order to do my learnings.

My advice would be to start with Data Specialization on Coursera - if you can commit yourself and learn from there, you can learn a lot. I found the discussion portals to be very useful. I would not suggest Analytics Edge until you are doing the learning full time - I found it to be very intensive.

If those option don’t work, you can always fall back on Jigsaw.


Hi Again !

Thanks for the quick response and clearly outlining the commitment level required for both the tracks.
I am enrolled with Coursera, but the pace of this course is very slow, and since there are dependencies one can not enroll in multiple courses from Data Science Specialization simultaneously . The Analytics edge would be more fast paced as it is spaced out in 12 weeks. (Starting from March 03, 2015)

While updating my knowledge on analytics training providers and related course offering in India by reading AV and other blogs such as AIM, I came across a certificate program, i.e. CPEE by INSOFE, Hyderabad.

According to AV rankings CPEE is mentioned quite down in the list. While gathering information on CPEE I could see that it has got a mention in the CIO magazine’s list of Big Data Certifications which will add value to one’s CV.

Kunal, would you be kind enough to elaborate if CPEE is a worthwhile option to help someone switch career to Analytics Industry.


I would rather suggest Analytics Edge.

Also, nothing stops you from enrolling for multiple courses simultaneously.

If you still need more information, I can put you in touch with a few people undergoing CPEE



Thanks again for the prompt response. I am enrolled for The Analytics Edge at Edx. and looking forward to it.

It would be great if you can help to connect current / previous students of CPEE.