Introduction to Machine Learning

I took it some years ago and made it to the MNIST digit recognition. I was thinking of picking it up again a few steps before that, using Python.

But I just started auditing/watching the Coursera Duke University machine learning class, which has graded quizzes I can take, and it is blowing me away (in a good way).

It really gives the big picture in a way I did not 'get' when I first took the Ng course. I may fly through it and then get back and code up the Ng course; I am not quite sure, but I want to / need to do some coding also.

Another idea is to do a number of hello-world projects using various datasets like MNIST and Iris and some text data, and using various ML algorithms coded from scratch in numpy.

What is the best online Machine Learning course for someone who doesn't know anything about ML, but has a very solid mathematical and programming skills? I'm interested in applications to financial engineering, so that's probably more about regressions and less about things like natural language processing or neutral networks. I know Stanford's course by Andrew Ng is highly recommended for beginners, however its practical part is in Matlab and that seems outdated. Are there more up-to-date alternatives? What about Duke's course? It's in Python, but the syllabus seems to be skewed towards neutral networks and natural language processing and I doubt it's directly applicable to finance. All in all, please recommend me a good online course in ML for a beginner with financial engineering applications in mind.

I chose this one https://www.coursera.org/learn/machine-learning-duke