For an undergrad student of computer science, this course provides great insights into the world of astrophysics and how machine learning can be applied to solve some of the greatest mysteries of the universe.

nice starting point for graduate students or senior undergraduate students who want to dig deeper in this direction

Some assignments are too abstract and difficult to get through without external help

This course was walk in the park in comparison to the other ones in the specialization. However, it would not be so if I did not complete all of the previous ones. Non-perfect score goes because I think that practical assignments should be better explained like: "do some feature engineering", "feel free to use any models", etc.

FUN !!!!

The course material is quite brief and introductive for particle physics, with only a few interesting machine learning tricks. Meanwhile, the assignments are less prepared even misguided, either need blindly tuning sklearn optimizer or heavily dependent on feature engineering, which are not related to the core knowledge of the session. From my point of view, this course is not as good as the other ones in this great machine learning specialization.

A challenging ML course for practitioners and researchers to put their abilities to the test. Could have enjoyed a bit more (possibly optional) explanation about the underlying physics.

Awesome Course! Puts everything in perspective with real world and real experimental data. Those who understand the real value of the data and understand the importance of the data would certainly enjoy this course. Thank you for organizing this last course in the specialization.

Vary hard, and very exciting, But I wish some lectures about the algorithms itself. And reviews about the work in reality vs the slices of the datasets.

Very nice overview!

Especially for an ex-experimental particle physicist being out of that business for more than 20 years.

This course is really good...

Excellent !!!

Great!