great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

This is the worst course in the specialization. The autograder is bad. There is inadequate explanation about when to use the different models. Presumes way too much about the student's level of knowledge. Would not recommend.

There's too much back to back to back video lecture and not enough hands on work. The final quizzes and projects are too challenging given the amount of work done on the subject matter.

Very poor configurations. I am tired of submitting assignments on auto grader. This is the first time I am having such terrible experience with Coursera. Hope you improve.

No visible support from groups forum. Videos knowledge is limited to complete assignment or quiz.

This is my worst experience of submitting assignment and I found out that I'm not alone

The guide could not explain the concepts well. He was just reading from the slides.

Bad teaching, unclear explanations.

I learned half of the material from Youtube.

this is the worst course ever. so bored and frustrated

Terrible quiz problems and grading mechanism

Lectures were good, direct, not too complicated to understand and conceptual. I suggest though that maybe visuals on the lectures could be even better. Assignments were reasonably difficult and forums were great to review the problems and find solutions for the errors. Thank you for this course

Good class with a lot of interesting material. However consider correcting some issues like, each exam we are told to read file from the folder readonly and each time I got 0/100 at my first submission because the file was not in this folder!! Anyway, quality was present.

Honestly this course was somehow disappointed I really wanted to learn a lot but the professor was somehow discouraging, he repeated himself a lot, and for an online course and every video been 20+ minutes long and at the end only been useful 4 or 5 min of it… having so much errors during lecture and not following the notebook as it was given to us make it more difficult to learn… I’m choosing this platform (and paying) due the professor been good and this one make learning more difficult than the previous one.

I think this course would be a bit challenging to someone who is new to machine learning. The professor often glosses over import details and moves a bit quickly through the course material. There needs to be more powerpoint and reading material explain what the videos explain.

Unfortunately, for me, this course (not the specialization) seems to be a "review of" Applied Machine Learning in Python" rather than "teaching" Applied Machine Learning in Python. Some codes used in the notebook were skipped by the instructor.

Week three is the worst ..

Lecturer is getting confused a lot in an already confusing topic which ofc makes me resort to outside readings in order to grasp it and leading to stretching the time I need to finish this week

Teachers are very mediocre. They make way too many mistakes. Their pronunciation is stoic and muffled at times - makes it hard to follow.

The video and training provided it's not providing enough information in order to complete the assignments.

I had high hopes going into this course after the really well put together courses 1 and 2 in the specialisation, however the video material was dull and disengaging. Where the lecturer could have spend hours going into the ins and outs of how the different algorithms work, instead the course followed a structure of: 1 - Brief overview of an algorithm, 2 - whats the syntax in scikit-learn, 3 - what parameters does it take, 4 - what other commands are there

I was really disappointed, as most of the actual learning was done from reading other sources on the web and watching videos for free on YouTube. I guess the only positive is that because I paid for it I was forced to finish it?

I'm disappointed that I took this class, poor design and delivery. Machine Learning is an exciting and fun topic, but you'd never guess it from this class, and the way the instructor delivers the content. It's a shame that the designers want to throw every possible model at you in 1 or 2 weeks, before having a discussion on model evaluation. This course focuses more on the academic than the practical, and doesn't try to explain these topics in an approachable manner. There are far better and engaging options available.

This course is all over the place, and compared to the previous courses in this specialization, this seems like more of an effort to gloss over the documentation and capabilities of SciKit Learn rather than focusing on a handful of the most important ones. The course lacks focus, the material taught is not rich, and you are better off just reading the documentation on your own. The book recommended at the start of the course is excellent, and reading that instead might be more fruitful for you.

worst course of this specialization so far , the instructor is just reading stuff not making any effort whatsoever and it seems like he's obliged to do teach this course ,the autograder is the worst and the journey with this course is really painful i hope that you take these points in consideration and just delete this course

The materials of this course is poorly arranged: how is that even possible to cover gradient boosting, random forest, neural network, and unsupervise learning in a single week?

This is a really bad quality course. A little bit more professionalism would be advisable. I will continue to the next course and leave this behind.

Faced problem in every assignment while reading the data sets. If the data is not in that folder what is the point of telling so?