The course is well balanced but the progression becomes quite agressive at Week3 and culminate at Week4 with a real life case assignment without much guidance. Great experience dough.

Amazingly explained. An intermediate Machine Learner would definitely get clarity of concepts already learned and also new concepts explained so skillfully with graphs and diagrams.

Good overview of methods in ML. Would have been nice if the lectures contained a little more mathematical rigor and explanation of why and how the various algorithms are effective.

Good course and prof.

The exam and exercise in very interesting according to what I learn in following all videos, with this i improved my level in python progamming, I recommended.

Automatic assignment grader has room for improvement. Some python code that works perfectly well when run locally or on the course web page would crash when run by autograder.

The class material is well prepared and make machine learning very easy to learn. The first three homework assignment is a bit hand-holding but the last one is really good.

Good Course, i would have liked a little bit more theory about the algorithms, but this is an applied course of ML. Projects are good and the readings are interessting!

Videos are good and had challenging assignments. I enjoyed learning new concepts. I wish we had one more week to practice more on advanced Machine learning concepts.

Very interesting, a lot of focus of statistica theory and little less (as compared to previous courses of specialization) on practical examples and implementation.

Good overall but some concepts and python functions need more explanations. Maybe 5 or 6 weeks are more appropriate for this course. It is too dense under 4 week.

better than the first two courses of this specialization for the content is coherent and the assignment is relevant to the knowledge taught in the course video.

Request: Can we have the instructions with a "translation" to "regular" English - for those of us who still have to get used to machine learning jargon? Thanks.

Code and examples were very useful. Teaching a bit lengthy and detailed at times. Overall a very good course for getting hands-on machine learning in python.

It's alright as a course focusing on applied techniques. If you are expecting more theories and understanding of the algorithms, this one may not for you

Vary good course, vey well explained, the only problem I used to have was about the assignments, there were some ptechnical problems with the files

the authors can include more coding questions so as to not only help a student to learn Machine learning but also become fluent in implementing it.

Submission isnt easy often gave errors that are not due to students' faults. Time-consuming unnecessarily. The content and assignments are great.

Very informative course, the only issue I had was with the file locations in the assignments. Takes up a lot of time switching back and forth.

There are some problems with the assignments but the course is very good. You must improve the material for the assiggnment. I love the forum

Knowledgeable teacher but still need to improve some presentations to limit the need to get extra resources for understanding the materials

Good overview of machine learning topics with practical exercises in the use of multiple techniques primarily through use of scikit-learn.

Hands on and practical. Dr. CT and his staff have done a great job introducing Machine Learning. Where were you 20 years ago? Thank you!

A good course for beginners in Machine Learning. You get to the learn the basics of many techniques and their implementation in python.

Excellent lectures. However, I would have needed more guidance for the last assignment. I learned a lot, but through pain and struggle.

It was a great experience learning through Coursera ,who provides best faculty for making students understand easily.

thank you Cousera