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Kursteilnehmer-Bewertung und -Feedback für Deep Learning in Computer Vision von National Research University Higher School of Economics

219 Bewertungen
55 Bewertungen

Über den Kurs

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and often demonstrated in movies and TV-shows example of computer vision and AI. Do you have technical problems? Write to us:



Jun 12, 2018

Excellent course! Quiz questions are conceptual and challenging and assignments are pretty rigorous and 100% practical application oriented.


Apr 19, 2019

Don't just read what's written on the projector. Try explaining it. And explain with code.

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26 - 50 von 53 Bewertungen für Deep Learning in Computer Vision

von 111qqz

Jun 30, 2019

Poor English pronunciation, strange tone makes this course very difficult to understand

von Edgar I

May 17, 2020

Very good course!

von Nandini

Apr 19, 2019

It was good

von Roman

Oct 23, 2019


This is an advanced course. Most of the time it would be difficult. In general, this course looks like the whole educational system in Russia - the given task is much harder then you can solve right now. But if you had a strong motivation you became much smarter. Support for this course doesn't even exist, but sometimes it is very useful to read the discussion to week practice.

Lectures and quizzes:

Teachers try to give a LOT of information in a very short time. But this theme is really not as simple to be told quickly. So as a result, you can understand just nothing:) Additionally, a heavy accent and kind of advanced vocabulary can make you feel frustrated.

BUT you can look at this that some keywords to google it was given) So generally, to understand I spend a lot of hours of reading about approaches in Computer Vision, mentioned here. The course was very useful from this point of view.

Quizzes sometimes look like crap. For some tasks, I still don't know to answer correctly.


This is a part which could you a reason for you to finish this course. Tasks here really hard and requires from you a lot of time (about 20h, including the time to understand the task itself). I highly recommend all this practice carefully, it could be helpful for you in the future;) As a result, I knew a lot of tricks on how to prepare a model for find, recognize and even create faces.

von Erik G

Jun 07, 2019

Some lectures aren't clearly structured. The homework assignments have downstream dependencies (week 5 depends on earlier weeks) which is not the best format IMO.

von Wei X

Aug 31, 2018

Nice introductory course. It include many background knowledge of computer vision before deeplearning and is important to know.

von Mallikarjuna R Y

May 08, 2020


von Saptashwa B

Apr 20, 2020

I'm usually very kind and upbeat so, writing this review gonna be hard. But let's start with the positives

Pros :

1. Fantastic real-life assignments, which require knowledge and coding ability to build and fine tune realistic deep learning models.

2. Rather new concepts are being presented (or at least shown on the slides) which will give a non-computer vision engineer a glimpse where we are currently now beyond cat-dog classification. So to understand the new stuffs it is necessary to take steps on your own.


1. The forum is dead! No instructor, no one from the university/department takes part in it to help answer some basic queries. I'm not so sure what's the point of having instructor or a discussion forum when they are of no use.

2. I feel for the students who take the courses offered by the instructors! It's so boring, they just read from the slides and no clear cut concepts that are necessary for the assignments are discussed. The instructors talking is just as useless as my exes when they used to argue with me. Useless!

3. I kinda feel scammed paying for this course because of the two aforementioned reasons.

4. Sometimes the length of the videos are long and concepts presented are so unclear that, searching and learning by myself would take way longer than estimated time of 1 week. So if you really want to learn all things taught and solve the assignments by yourself, you are in for a hard ride.

So that's all! I have already finished two of the other courses in this specialization (Intro and Bayes), and they are way better so, hopefully the experience with the next course in this specialization won't be as horrendous as this one. Fingers crossed!

von Jiachen L

May 05, 2019

Course homework is actually not well designed for Coursera platform, some homework is not quite relevant to Deep Learning (i.e., HW1 and HW2) and some is very hard to complete (i.e., the last one, I tried on CPU for about 2 weeks). Also, the slides are not shared for this course in the series.

von IMAD E M

Jul 10, 2019

pretty good mooc wtih very exciting and hard assignments, I highly recommend it. The main issue I faced it was that the lectures are not well explained, so you need to look for documents and other lectures by yourself.

von Anmol G

May 02, 2019

The content was good, but there are several drawbacks too

1 Content not explained well

2 Assignments had mistakes (like broken links, wrong descriptions)

3 Minimal or Non-Existing support from the staff.

von William

Apr 22, 2019

The task is really practical and useful, but the courses content is too general and I hope for the future it could include some papers reading assignment

von Igor P

Mar 25, 2020

Overall it's a good course, but needs some improvements to make tasks clearer and provide a fair evaluation.

von Gary

May 27, 2019

Not clear. And just focus on papers, not on basic structure or models.

von Marian L

Aug 08, 2019

Zero passion from instructors. A lot of stupid questions, some of them with errors. Interesting programming assignments, but with dozen of typos. Don't expect to finish any of those programming assignments in two hours.

von Liu

Mar 03, 2019

no lecture slides, the lecturer cannot elaborate his point clearly (or he doesn't want to), the projects seems ok, but they also are in lack of hints for me to gain progress

von Francesco Z

Sep 26, 2019

Course is poorly mantained. Time is spent to understand what it is to be done rather than learning. Some bugs in notebooks are not fixed. Not a good experience.

von Иванов К С

Apr 20, 2019

This isn't a good course, difficult to understand and don't maintain by authors.

von juehuan l

Apr 07, 2019

Some lectures are just reading the teleprompter!

von Nabarun D

May 20, 2019

Worst course in the specialization.

von Shashank P

May 07, 2020

very difficult to understand

von Nguyễn M T

Jul 16, 2019

not clearly content


Apr 26, 2020

This is a very poorly made course for Computer Vision, as it roughly teaches you 30 minutes of theory and expects you to answer the toughest of tough questions.

von Korutla R

Apr 14, 2020

Worst course

Worst teacher explanation

Worst planning

No resources in it

Worst worst worst!!!!

von Bhanu T B

Jul 07, 2019

This is not a course,it is just a man giving his presentation.