I successfully completed this course with a 96.7% mark. It was fairly easy given my experience so far in machine learning and deep learning, but there were a few new ideas that I learned here and also others that I investigated in greater depth out of my own curiosity while doing it. I felt like the Transfer Learning, Multitask Learning and End-to-End ML lectures are not really useful immediately after the course unless one takes these up after the course in greater depth as the lectures on these topics were quite superficial and brief. The practical advice, however, and the hand-on exercises that focused on real-world scenarios were useful and I wish there was more of the latter (perhaps optional) in the course.
Here’s a link to the certificate I received from Coursera for this course.