Coursera’s Data Science Specialization Track

In my year-end post for 2014 I posted about Coursera’s Data Science Specialization Track and after that a couple of people have asked me to give more details about these coursers and share my experience in taking them.

In this post I will give more details about this sets of coursers and about my experiences so far in taking them.

Data Science Specialization course information

Data Science Specialization Track is a sequence of coursers that are available in Coursera. These coursers are developed and conducted by professors from the Johns Hopkins University.

The following is the list of coursers that are covered in this track.

  • The Data Scientist’s Toolbox
  • R Programming
  • Getting and Cleaning Data
  • Exploratory Data Analysis
  • Reproducible Research
  • Statistical Inference
  • Regression Models
  • Practical Machine Learning
  • Developing Data Products
  • Data Science Capstone

Each course takes about a month to complete and it is recommended to be take them sequentially since the later ones are dependent on the earlier ones. The last one is not a course but a Capstone project which allows you to use the skills that you have learned in the courses.

Signature Track

There are two options to take the coursers – normal and signature track. Normal is free, but you will not be getting a certificate. Signature track costs around $29 per course and gets you a certificate.

My experience so far

I have completed the first 4 courses and I am doing the 5th this month. I opted to do the courses in signature track, since paying for them in advance gives me some motivation to complete them. I think this is more important for me than the certificate itself 😉

These courses consist of video lectures which you have to watch every week and then take the weekly quiz. There are also one or two projects per course that will be evaluated by peer review. Doing peer review gives you an opportunity to learn from other people’s work. Also I found the forums to be very active and I have learned lot of things by interacting in the forum.

On an average each course takes about 4-5 hours of work a week except the first one which was very easy and took me only about 5 hours in total to complete it.

I don’t have complete notes for the first 4 courses, but I am planning to take notes for the remaining courses and I will post an article as I complete them.

Will I recommend it?

Will I recommend it to you? Well, that depends on your experience in Data Science and how motivated are you to learn it.

If you are interested in Data Science and don’t have much experience in it then I will recommend this set of coursers for you. But keep in mind that it needs a serious level of commitment since it takes about 5-6 hours a week for up to 10 months to complete the entire track.

If you already have good experience in Data Science then it may not be very useful for you.

Do you like any other courses? If yes then kindly share them.

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2 Comments so far

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  • John Amirtharaj says:

    Hi there, I’m from TN, India and working for a Bank here in US and I’m tasked to learn Data science and help the company, based on your blog it looks like if anyone is serious and committed this course should help, please explain more to it, because I would like to be committed to it ( and it expects at least 6 months if I can do 2 courses in parallel ) and I really need to know if all these individual courses are very key to get into Data Science and instructors are talented to get the most benefits. Thanks

    • Sudar says:

      Hello John,

      If you are completely new to data science then this course will help, but just learning this course will not be make you an expert in Data science.

      This entire course is slightly demanding (especially if you have not programmed before) and it may be slightly difficult to do them parallel since each course requires knowledge from the previous course.

      But you would be able to do the first few ones in parallel.

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