Ratings and Reviews for Applied Machine Learning in Python

It was really hard, but worth it!

Amazing module. Clear explanations and useful examples and exercises.

Great course! I have learnt a lot of machine learning skills from this course. Regression, classifier, metrics, clustering. This course cover both theory and practicing. The

Excellent instruction and challenging assignments! Sophie from the teaching staff was very helpful and responsive to forum posts. Thanks to Kevyn Collins-Thompson for a great survey course in machine learning. The only downside was that the auto grader has limitations which inhibited some exploration (one can not keep plots in the submission is an example), but I'm sure that will get worked out.

Really good course. Lectures and Assignments are very interesting.

I learnt a lot about machine learning - great assignments as well

I did this course only from the entire specialization so it was a little hard to catch up but the difficulty made me even more excited to keep going and finish every bit of the course. I really appreciate the amount and quality of content, quizzes and assignments. Totally worth my time. Thanks UoM and Coursera!

I learned a lot from this course, but I do not feel like I truly understand everything. There was an extraordinary amount of information that made it difficult to keep on track and take everything in, not to mention apply the concepts in the assignments. I feel confident with the concepts and I could do much better in the future with more practice with skills developed from this course.

Clear, smooth and awesome course. Had fun learning the theoretical stuffs . Assignments and quizzes are really helpful in understanding the concepts. Last assignment helped a lot in applying the things learned in this course

Very informative about machine learning approaches ie supervised and unsupervised learning. And then goes into detail about the techniques such as regression and classification for supervised learning and clustering (K-Means) for unsupervised learning. Other techniques are discussed such as Principal Component Analysis etc. I enjoyed it and would recommend for all data enthusiast.