Microsoft working with edX.org has created a data science track consisting of 15 different online courses. Ten courses must be completed with a passing grade in order to complete track. The final course is a capstone machine learning project where a minimum score must be achieved. This week the capstone course, which started in December finally completed. With a passing score in the capstone course I have finished all of the certificate requirements.
The Microsoft Professional Program data science track is for those of you who are either making the move into data science or wanting to learn the Microsoft stack for data science . There are 9 classes you must past. Most of the classes are required a few have optional paths. For example, there is a choice between a more advanced ML or an Intelligent Apps class. Those tracks that have a programming aspect allow the viewer to choose R or Python. In the 9 courses, the student will be exposed to R or Python, statistics, working with data, machine learning in general and Azure ML. It is well rounded set of courses that focuses in on the machine learning aspects of data science.
The program will not make you a seasoned data scientist. There is simply too much to learn to fit it all into a single track. It will give a solid base to build on. There is a final capstone where you will be expected to put what you learned into practice. The program packs in a lot of concepts and hands on work and it does take some time and effort to complete the program. Interested in knowing more about the program, leave me a comment!
Click here to Learn more about the Data science track.
Congratulation for this achievement!
I just started the Microsoft Professional program in Data science 2 days ago and I am expecting to complete it by next month. I am a MSCA SQL server 2012/2014, MCSE Business Intelligence, MCSE Data management, and Analytics. This program seems to me like an excellent training to prepare the actual Microsoft certification in Data science that I have been waiting for so long. I took a quick overview of the curriculum for this program before starting and I think it is worth taking it.
I really hope to complete it very soon. Thanks for providing this useful information about this program.
No problem, Thanks for the comment.
What chances are in getting a rewarding job once I am getting this certificate? Any idea about the salary average, and chances to go further with Data Science. Thank you guys.
I think the reward for the work is really an “It depends.” Location and background history is probably really important. Does this replace a phd in Math or Stats? No, but it gives you some good hands on training with some theory.
Congratulations Darrin!! Well done!!
How long it took to finish all the courses since you started the first one? How much time per a week is required?
Thanks. It took months to complete the entire program because the classes start and stop on a schedule. I did it pretty quick and I probably spent a 4-6 hrs per week overall. The final project went in spurts as I came up with new ideas to try. Good luck.
Darrin, can you please tell me more about the final capstone project? I am about to star it next month and would love more info and any tips that will help me pass.
What can I expect from the final project?
We had a beta trial on the final project, so it was a little interesting. Lots of people were looking for very high returns but in reality we did not get amazing numbers. Just watch the leader board and try to keep up or average with the others. For many, the trial numbers were very close to the final checks.
Hi, Darrin, i have the same question. could you tell couple of words: what kind of tasks in the final project, how you can choose them (if you can choose them), time required to finalize the project.
I am expecting to take part in October and would like to make some preparation in advance.
Irina, For my trip through the program we were given a project and could not select then project. Its been awhile but the basics of the final… we were given some data and we were to create an experiment that had to pass a certain mark. There was 3 sets of data. One that we got to work off of ( and we split that for training), one to “test” against an unknown subset of data to see if we over fit or not and the final set which were were graded against. The trick was you ran many experiments trying for higher numbers and if you passed the set mark, that did not guarantee a passing mark on the unknown data ( think overfitting). We were allowed to mark 3 experiments to submit at the end of the course and those three were run against the hidden dataset.
Time depends, I got to a “passing” mark quickly but spent a lot of time trying to increase my accuracy to make sure I passed the mark when it came time to grade. Hope this helps.
Is evrey person who is taking MPP will get “Charter Member” award??
I suspect not. It has been sometime since the data science program ran. I don’t think charter member makes a difference anyway.
Hi, Great article! I’m currently doing the course and not sure whether to go for R or python. I dont have any background on R or python, and am currently a marketing analyst, but want to switch to data analysis.
Could you please guide me as to which path to take?
There is no right or wrong answer, unless you get a job for someone who has already decided R or Python for the company. Most people who are just starting out seem to go the Python route. I went the R route and then backed it up with Python. My dev background makes it easy to jump back and forth. R can be slightly different than other languages and Python seems to follow a more common development language. R seems to be more common with statisticians and those who had formal education in data science. In the end you cant go wrong with either one, R and Python is just a language and its what you do with the language that really counts.