Back in October 2016, I finish the Machine Learning course by Stanford University on Coursera. It took 3 months to complete and I learned about the theory behind the basic machine learning algorithms. (ie Linear Regression, K-Means and Neural Networks). The course provided a broad introduction to machine learning, data mining, and statistical pattern recognition. Matlab was used throughout the course to implement algorithms. However modern machine learning frameworks are written in Python, R and C. Overall, it was fantastic course that I would recommend to any software developer interested in ML.
Lastly, if you’re still not sure if the course is right for you after checking out the syllabus, then watch this video.
It provides an excellent overview of most the lectures in 30 minutes without the math.
A Friendly Introduction to Machine Learning