This course is a good first step of the specialization in machine learning. It provides a very loose overview of what is going on. Each week one lecturer explains the "idea" behind a machine learning algorithm, then the other one implements parts of it. For the quiz you're required to use the output to find specific data results, or add some minor feature changes. The lecturers in general do a good job and the lectures are well structured, with the welcome occasional piece of humor.
I personally found the course to be completely overshadowed by Andrew Ng's Machine Learning Course. This course makes use of a highly specialized tool: most of the time the actual "machine learning" part is done by some already built-in algorithm of the software, and almost all the work we do is in data handling. While I'm sure this is great for some people, I would hesitate to describe this as performing Machine Learning ourselves. Similarly, while the tool is excellent and I'm sure people use it in the industry, I went into the course hoping to learn more about the fundamentals of ~how~ machine learning works, which wasn't covered too well. It's quite likely the later courses cover this as this is the first in a specialization, but for anyone other than a beginner you might experience these same concerns.
The quizzes being multiple choice is also a little aggravating. By comparison, many other programming courses have code submitting and marking tools, and it makes this course feel somewhat unprofessional at times.