Well explained - but I already have an image processing background. Providing a bibliography/list of references at the introduction of each lecture could be helpful (as in reading ahead of the lecture).

Very difficult to follow. Material is very technical and the lecturer simply reads from the slides. The volume of the recording is very low as well.

This course provides a good base upon which you can build your remote sensing knowledge. It helps if you already have a background in CS or maths (preferably a degree in one of those two fields). Starting in the second third of the course, the lectures fluctuate between very easy going to profound mathematics. Don't be fooled by the week time needed estimations - following this estimations you will get just a basic understanding, which will be enough to complete the quizzes, but for a better understanding of lecture material, be prepared to invest 2x the estimated time.

In my opinion, this course was a bit too mathematical and monotonous, the professor for sure knows what he is talking about but after having finished the course, I am missing a few more examples of how to use the concepts in practice / with a software.

The course comprehensively covers the domains of remote sensing and associated machine learning techniques and has aided me significantly in putting those techniques in practice for my startup endeavor.

Professor Richards is an amazing lecturer and the classes are very well structured and presented.

The quizzes are difficult for me. Im just relieved that theres no computations in the quizzes. But i learned a lot. Theres a lots of technical stuff so theres a need to read more about the weekly lectures.

Excelente curso. Introduce los sensores remotos como herramientas en la interpretación de la superficie terrestre de acuerdo al área de aplicación, haciendo énfasis en la geología y la agricultura.

A bit challenging but very insightful!

I learn more about remote sensing.

The course should add practice exercise for gaining more understanding to the course

Though the course is interesting, it would have been much better if the instructor was present while explaining the concepts which would give a classroom effect.

Excellent course! I thoroughly enjoyed the content. The course was well structured and the professor excellently. explained most of the machine learning algorithms in the context of remote sensing applications. I am quite disappointed to see the reviews of my fellow learners rate the course -low. I would like to stress it to the future learners thinking of taking this course to confidently enroll without a doubt. I agree that the concepts are quite hard to understand and may need an active learning mindset.However this course is the ONLY course which has tried to intuitively explain the application of machine learning to remote sensing datasets. Furthermore, the professor (John richards)is a legend in the field and we need to appreciate his passion for the subject and his effort to disseminate knowledge to students!

Cheers!!

T​his is a great course for inisiation in the remote sensing field of study.

Really enjoyed the learning experience and was very concise!

very imformative course

Absolutely informative

very useful

good

Its a very technical course and very advanced. It actually exceeeded my expectations and it took me a very long time to fully undertand everything (especially because I had a lot of difficulties with the language). I was expecting a level-user course, but it was far more advanced.

It's a really good course, and the teacher explains everything very well and in an understandable way despite of the difficulty of the course.

The course contents cover Remote Sensing but since the mentor is just like reading, just show the scripts, it's so boring. It will be better and perfect the practical exercises are added. And the course title should be changed to "Mathematical Calculations and Machine Learning in Remote Sensing". The beginner of Remote Sensing should not choose this course.

Very difficult to understand in the online format.