Courses to take in Machine Learning for applying for PhD in ML? I just finished my BSc Hons. in Mathematics and CS from one of the leading research institutes in India (Not IITs). Now I'm going to continue my masters in CS. I like ML. But I haven't done any proper course. I wish to apply for PhD in this area. Can anybody tell me a detailed idea about the courses that I need to take so that I can apply for PhD in US or Europe?
Can anybody tell me a detailed idea about the courses that I need to take so that I can apply for PhD in US or Europe ?


PhD programmes in the US and Europe are significantly different. While a PhD in Europe expects you to have a fair idea of what you intend to research, the US universities allow you to take courses to learn - quite similar to what the IITs follow.

What courses to take largely depends on where you are studying, right? You cannot take a course if it is not offered.

An example Data Analytics course is at https://volgenau.gmu.edu/program/view/20521

Basically, you want to learn a couple of programming languages - Python (with scikit-learn) is good, take a course on statistics (and learn R programming). A core course in Machine Learning (teaching decision trees, neural networks, clustering etc.) and few courses on database systems. You need to know SQL and also NoSQL systems. Try MySQL and MongoDB, for example. These should generally give you the pre-requisites. 

Also, just learning theory is not enough - one needs to also do practical work. For that, I would suggest learning Linux and having the ability to spin up VMs and setup a system with Hadoop etc. Cloudera provides a VM to get started, and so does MapR. Virtualbox is a good free virtualisation software.

You also need to decide what field of ML you want to go in further. This would depend on whay you want to learn ML - the reasons would be your own. Of teh sub-fields one could look at pattern recognition, audio recognition, predictive analytics, classification systems etc. You should then do your Masters work on that. IMHO, it would make sense to look at small, real world problems and try to solve them with ML to build a portfolio, then tackling something huge. If you are able to solve small but significant real-world issues, you would have a much better chance of landing the paid scholarship.

To get an idea about opportunities available in the UK, you can join the BIG-DATA@jiscmail.ac.uk mailing list. Social media researchers can join mailing lists of the  Association of Internet Researchers at http://aoir.org

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