Specializations are new multi-course programs. In case of Data Science Specialization you will take 9 separate courses with signature track for $49 and earn certificate. And complete track you can finish with capstone project which is another $49. So, if you wanna be certified for Specialization you need finish 9 certified courses and do final project. In total you will pay $490, but it is in 10 separated payments. Great thing is all of these courses are under patronage of Johns Hopkins University which I hope ensures quality. I need to say that based on my experience with Computing for Data Analysis course which is done by this university as well, it has really good quality!
Course list is here (order in recommended study order):
- 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
And 10th of course capstone project.
I have to say, I am really excited someone start with this idea and prepare something reasonable, so I will definitely join.
I just see few topics untouched (and correct me if I am wrong) and I thing this are a part of Data Science too:
- Business insight (why is it needed from business perspectives, what's are expected results and other business related questions)
- Store and retrieve data (incl. Big Data and usage of NoSQL databases - different kinds of)
- Big Data and its scaling and parallelism (so application of Hadoop, MapReduce, etc.)
- Ethics of data and its privacy and security (anonymous data for development, public vs. private sources, cloud storage of non-public data, and so on)
Fulfilled boxes are already proposed terms on Coursera, dashed ones illustrates possible prolongation into future. |
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