I enjoyed learning about Computer Vision . The course showed me a new horizon and motivate me to discover this filed more. Thank you to All the professors ,and thank you Coursera!

This course is a good course to start computer vision for beginner level student, and I offer This course to everyone who is eager to learn computer vision conceptually.

Nice Course. I'm very hard to study and practice to passed the assignment. And that could give the experience on matlab including Image Processing skills. Thank a lot!

This was an excellent introduction to computer vision. I especially appreciated the various extra resources and in-depth explanations of how computer vision works.

Very wonderful Experience . Got to learn so many new concepts starting from basics of Camera to the vast application area of CV. Very good coding assignments.

The basics of computer vision theory is well covered. The MATLAB exercises are bit tough but once you try them you can crack it.

it is a good starter for those guys who want to start learning computer vision for Robotics, AI, Image Processing, etc.

Very informative course for beginner

Great Course

It is a good introduction course but I think some more demo coding for matlab in the first assignments will be a good thing so we don´t have to spend a lot of time on google and on trial and error.

Definitely recommended for beginners. This course insight from concepts to application.

Great course, but require higher understanding of MATLAB

As a complete beginner in image processing, I feel that more videos training the usage of MATLAB image processing functions should have been included rather than just giving assignments. A little more practical lectures other than theory would have been great.

Overall, I can definitely say I got a good idea about how human vision inspires computer vision and how much scope there is in this field in years to come.

Prior knowledge of MATLAB is required which is not mentioned in the course description.

Excercises seems to be a Matlab course, not computer vision

No similarity between lectures and assignments

Good information but a bit elementary.

Not good enough, atleast for me. The assignments were totally, totally different from the stuff taught there. Plus everything taught here was a vague theory which was not even remotely related to the assignments. Expecting better quality in the next courses.

The course definitely doesn't carry significant content and what after it.

after basics there should be some more courses for advance training.

The programming assignment were more than irrelevant.

sorry for the bad feedback.

but teaching was good

Not enough resources to learn from. Videos are not explaining the curriculum that is tested in MatLab "graded external tool". Forum discussions are far more helpful than the videos itself.

The learning does not prepare you for the assignments and all assignments are either pre-solved or cannot be solved without a lot of trial and error, no logic.

Not in depth knowledge provided , just gave overview of various topics in short videos , reading material is better than the videos provided.

If you want to pass this course, you must really know how to use MATLAB!

completely unrelated content and assignments

My first bad experience with Coursera content. It pains me to write this review, because it is always difficult to criticise other academics. The video lecture content throughout this course is very generic, like what one might hear about computer vision in a TED talk or on TV.

One speaker's body language was very distracting, another's pronunciation is hard to catch and many slides are tackily animated, so I ended up reading the video transcripts instead of watching them. Most videos are 2 or 3 minutes long, and there aren't that many videos. It's almost as if somebody forgot to upload the rest of the lecture videos!

The videos mostly contain introductions, applications and information surveys about various aspects of computer vision, with kitten and puppy pictures thrown in as "examples" to keep you interested.

The student grapples with fairly complex programming assignments with no idea about where to begin. Each quiz contains only one qualitative Yes or No question, which was not related to the video.

Though the course teaches you almost nothing about computer vision algorithms, it does squeeze in a few interesting minutes about human vision and basic optics, but that is not what a student who signs up for this course expects to learn here.

The math section (one week's worth, out of four) is made up of four or five 1-minute videos about the importance of linear algebra and calculus, but there's not a single equation in sight. The supplementary material for the entire course consists of either Wikipedia pages or research papers that the lecture content does not prepare you to read and absorb.

Even if you are a more senior industry professional interested only in a top level understanding of computer vision without getting into the math of it, you won't be able to complete the course because the programming assignments require some serious math skills that the course does not cover.

All in all, not a recommended course for your time and money. If you are looking for some good learning, Andrew Ng's Machine Learning course here on Coursera is more interesting and useful for computer vision than this one!