Overall, an excellent course. It gives a great introduction to many of modern and old machine learning models, and a brief glimpse in dealing with unbalanced data; a subject you can freely explore on your own. The strongest part of this course are the guided demos, they are excellent to see things happen in real time, with many ah-ha! moments, and filled code you can adapt to other projects.

However, there's a catch; to me, a big one. The guided demos; although excellent, are flawed. If you follow the practices presented in the demo, you generate a lot of data leakage into the predictions. Specially when doing cross validation with gridsearch, since the training is not done with a pipeline. Be careful when implementing your own machine learning models after following this course.

This course is a next level after understanding classification machine learning model. All my questions had been answered with this module. The instructor is very great to clarify the whole python code used. Highly recommended course

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!

Keep up the good work. You guys are helping the community a lot :D

Complex topics are not explained properly. The instructor just reads off the slides.

The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.

Very good material and approach to Human Learning +5 :)

The course content is very great in the coding area and it is very helping. but a shortage that is clear is the theory behind every algorithm, the handling of it wasn't that much perfect.

When explaining data and algorithms , it should be explained well with many visualizations and examples , it is very confusing to just show a static photo and telling many explanations on it

It is an excellent course on Classification. The approach of the course is different from similar courses I had attended earlier. It presents different classification algorithms as a continuous whole with increasing degree of sophistication rather as disjoint ones. This helped in understanding the entire range of available options and how to apply them in different situations. The faculty was very clear and precise in his presentations. Many thanks to IBM / Coursera.

Pros:

- taught by the Elite

- state of the art

- diverse topics and learning material

- very clear and solid structure

- (partially) covering the mathematical background for each topic which deepens the roots of knowledge

- Python Labs with diverse coding examples and outlines

- a very logical connection to the courses which are predecessors (Data Exploration, Regression, ...)

Cons:

- there could be more exercises directed at the learners' coding and conceptual abilities

One of the best data science courses on the platform. It has theory and a lot of practical content. Also, learn a number of classification models and how to deal with some of their problems. I recommend this course. I am very grateful to the teachers and the entire team that prepared this material of such high quality. Thank you very much.

This Course gives me more informative techniques and tools that's used in this course. Coursera is the best platform that everyone can visit. And you can learn here Data analytics, Data scientists, Machine learning, Artificial Intelligence, and many other courses. Thank you Coursera, It is very interesting for me.

Excellent course . I have done a lot of data science courses on Coursera and this one by far is the most comprehensive course on this subject matter and the training examples in the notebook, all are very well explained. Highly recommend it to everyone.

Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.

If I could change something would be, to link the knowladgments that all students requiere with each corresponding links to access. Also the times are too short to really aqcuire the topics.

Well-structured learning path. If you dont have previous python experience you can catch up after a couple of weeks as the workflow is similar regardless of the algorithmn you are using

Excellent theoretical and practical understanding in classification algorithms. The instructor is really of a very high level and I appreciate his effort.

It's a greate course. I learned a lot, from deeper understanding basic algorithms to more advanced technique such as bagging and model explanability.

The instructor from videos is amazing. Great tutor. So far the courses from IBM Machine Learning Professional Certificate are really, really good.

Más perro de lo que pensaba. Si realmente quieres profundizar, vas a buscar otras fuentes para complementar lo aprendido en las clases.

I would like to give especial thanks to the instructor (the one in the videos) for his great job. It would be nice to know who is is.

A wonderful experience... learnt a lot and understood the rol of EDA, the method to evaluate classifiers with different metrics...

Super content and good practice, perfect if you want to get an overview of all ML classification algo including ensemble methods !

Well structured training. Lab sessions and assignments are well planned to get clarity on concepts and practical application.