Andrew Ng's courses are excellent. Another pretty good Coursera course is Machine Learning Foundations from the University of Washington. It is very high level and novice friendly. While it covers non of the math and very little programming it does give a nice quick introduction to the most popular ML techniques out there and when to use them. It all depends on what level you are interested in starting. They also have follow up courses that go deeper into the different techniques.

+1 for this recommendation.

I would specifically recommend Machine Learning Foundations: A Case Study Approach - It is fantastic and helped me greatly start my ML journey last year.

Turi is awesome, I hope Apple is doing something great with it.

Thank you! Should I start with the Machine Learning one?

From my experience Andrew Ng wiped the floor with every other lecturer I've had. Both the ML and his new Deep Learning course.

If the lecturers aren't very interesting Coursera can be as hard as any other lectures. I gave up on the Scala functional programming and disappointingly have stalled with Geoffrey Hinton's Neural Networks courses.

But I really can't understate how good Andrew Ng is, he has a very relaxed manner and manages to make some very complex topics seem almost trivial.

The worst of the mathematics is derivatives and matrix multiplication. You can even avoid matrix multiplication mostly in the ML course, but in his Deep Learning course he takes you through the 300x performance benefit you get from using NumPy and matrix multiplication vs loops.

At your level yes, I would recommend starting with the ML course. It is really beneficial to understanding how the mathematics work.

The two most important things to remember, since the courses are challenging: 1) don't be in a hurry, and 2) don't give up! Take the time to learn every detail presented, do the optional exercises, and dig deep.

It's definitely challenging. The math and just seeing the complicated formulas really push me, but the reward is good too. I'm tired of pushing pixels and doing some meaty stuffy like ML is a nice change of pace.

I would recommend starting with deep learning first since that's what you are interested in and it covers all the ML principles you need to be familiar with. If you want to go deeper and get familiar with other ML techniques too you can easily follow the old course afterwards.