Mathematics for Data Science

Thank you for your reply. What do you think about this course? Does it cover the math required for the program?

https://www.coursera.org/specializations/mathematics-for-data-science

Thanks a lot for your help.

https://www.coursera.org/specializations/mathematics-for-data-science

Is this math course enough to revise math?

Hey bud,
I have a few suggestions which helped master the math behind ML. I started out with the Coursera Course: Introduction to Mathematical Thinking by Dr. Keith Devlin.Link: https://www.coursera.org/learn/mathematical-thinking/home/welcome

I followed that up with a Specialization called Mathematics for Data Science.
Link: https://www.coursera.org/specializations/mathematics-for-data-science

These two took me around 5 weeks to complete. Post completion I was fairly confident with my Math skills. I also watched Videos on Youtube and referenced Khan Academy.

Hope it helps. :-)

https://www.coursera.org/specializations/mathematics-for-data-science?

You can take a look at this Coursera specialization, pretty much sums up the big topics.

You need to understand one thing, their entrance test is more to check, logical and analytical ability. Also, it's a time-bound test, so try finishing the test within the time limit and see how much you score to judge the level.

Secondly, the first semester of this Masters degree comprises of Maths and Programming courses (which other online masters degrees expect you to know beforehand) hence they can keep the bar slightly low, as they will teach it to you.

HSE is one of the top Russian universities and offers some of the most difficult/challenging courses on Coursera. If you want to get a flavour of what the degree will look like, you can start with their "Mathematics for Data Science" specialisation. This is part of their Masters in Data Science program.

In my opinion, this is one of the most rigorous online Master's degree offered right now. They have also collaborated with Yandex (Russia's Google, also check their Yandex School of Data Analysis) ensuring that the course will be practical and relevant.

Recruiters do usually not know the differences between those certificates and do not put much value on them. As mentioned by others, courses certify your basic theoretical knowledge, however practical experience, soft skills, and company fit are more important.

My advice would be to go with the more relevant, interesting course for you. The two courses you mention are quite different. The JHU course has a more high level, systemic approach to data science and tries to convey the ideas of system thinking and iteration similar to the book from one of the professors, https://leanpub.com/artofdatascience . The Python course seems more hands on and programming focused.

As courses are good for building foundational knowledge, I can highly recommend this specialization first: https://www.coursera.org/specializations/mathematics-for-data-science,

especially if you do not have a strong quantitative background. Those basics will suit you well when you continue into more advanced techniques and will give you an edge in stats & math interview questions.

https://www.coursera.org/professional-certificates/google-data-analytics

https://www.coursera.org/professional-certificates/preparing-for-google-cloud-machine-learning-engineer-professional-certificate

https://www.coursera.org/professional-certificates/ibm-data-science?

do these 3 for a LOT less money and you'll be far better off

then add

https://www.coursera.org/specializations/mathematics-for-data-science

https://www.coursera.org/specializations/mathematics-machine-learning