Needs to be improved with more math, more examples and problems. The course is okay but i feel it is more suited to students who have already learnt dsp and have come back for some revision. So not suitable to beginners at all. Math background should also be good before tackling the course. Plus having a dsp book to read things from is a must since a lot of the stuff is just briefly explained away.

Not good for beginners in DSP.

The video lectures are great, but the quizes are awful. The practice homework you are given doesn't prepare you at all for them and the quizes have zero feedback, so often you can't be sure of what you are doing wrong and learning from your mistakes is very difficult. If you add that the course and the quizes are quite mathy, it can get very frustrating. I can only recomend this course to people who already know the subject and want to refresh his memories, to very mathy people or to extremely patient people.

Course has potential and some of the material such as certain lectures and Python notebooks are very interesting and fun. Unfortunately the presented material does not prepare well for the exams and the student often has to access a myriad of other resources to even just understand what the exam questions refer to. This makes the overall experience very time consuming and frustrating. Unfortunately I don't think there are many alternative courses covering the same range of topics available at least on Coursera.

Excellent first look into DSP, especially in the context of Fourier. Fairly math heavy so a strong math background is recommended.

not suitable for people without prior dsp knowledge

Wonderful - all previous Digital Signal Processing courses I had taken (in a few different universities) had mainly left me confused with a lot of maths and only a vague understanding of the true interpretations and meanings of frequency domain analysis, or the differences between DFT, DFS, DTFT and FFT. This course is exactly the right approach for someone wanting to get real understanding and insight on how to apply these concepts to real problems. Even if there is a big focus on interpretation and understanding, the presented maths are rigorous and the lecturers are clearly experts of the field. It is a challenging course and you should be prepared to spend up to around 8h per week if you really want to work through the exercises with thought. The Python notebooks are a great addition as well - my only suggestion would have perhaps been to make these interactive graded exercises (e.g. filling in missing functions that implement some DSP algorithms). Recommended thoroughly and I will continue to the next courses in the series!

very good course, but it require some math and a brief reading of a book in signals, there are only few courses in coursera that are challenging, this is one of them, 10/10

The course have a lot of wasted potential, the python notebooks are great and the initial lectures are good but the following lectures are boring and short, meaning they are tedious and have a high density of information, making them very tiresome.

I can watch the videos multiple times, but i don't want to because they are boring.

I had to use multiple sources to learn the concepts, including my electrical engineering master's classes, and i realised that Digital Signal Processing (DSP) is badly taught overall.

The mathematical ideas are not hard, but the mathematical notation used in DSP is cumbersome, making it tiresome to get used to, a lot of different numerical explanations and examples are needed, these lectures don't give you that.

The image and audio quality are very good.

Here is an advice for present or future teachers, don't be afraid of explaining the same thing multiple times with different perspectives, it helps students create the mental model of the content, thats how you build knowledge in your mind, much better than listen/read the same explanation multiple times.

If you don't have any signals of systems background, course is not much explanatory. Also, to understand mathematical equations you should know the theory behind them very well before taking that course

This was a Mathematics Intuition packed course, very suitable for people looking to further their understanding of the Motivation behind technical terminologies and technique. I would love to point our some special point:

Vector Bases: This is the first SP class where i learn about vector bases, i learned about them in Applied Algebra but never really understand them outside of problem-solving. Prof. Prandoni explanation and examples "clicked" for me and helped me connect multiple concepts i never know are connected.

DFS/DFT/DTFT: Prof. Prandoni gave us very clear definition for each of them, help us define which terms is whichs - as well as their application - whether it is computational or mathematics proof.

However, while the course is strong in Mathematics intuition, there are some technicalities (especially in quizz), that are not included in the course. The technicalities can be solved by picking up your calculus (or algebra) textbook so it was not a big issue.

This course was a great refresher after not working with DSP concepts for while. It also went beyond what I had learned in school with good explanations and extra insights.

It is a really comprehensive course with quizzes that were a bit tricky and challenging. I liked the python notebooks for complementing the theory of the course

If you have enough patience to go through the math, you'll find this course and the subsequent courses in the specialization extremely rewarding.

Thoroughly engaging. One of the better courses on this platform.

Nice Course, lots of applications. math is challenging when proving a problem. But it is a great course to start up. i would integrate more the programming component in class although there are Python Notes in IPython.

The lesson is nice but I am disappointed about the practice part. Only a sheet of exercises not really progressive, it would be nice to have some directed work. Often the mathematics aspects are not enough detailed and, maybe I don't have enough background, but it doesn't look like a lesson for beginners. I'm also disappointed to have to get some external contents to succeed the evaluations. Finally, I spent something like 100h on this lesson and most of this time was not on your platform but by reading book or watching tutorials...

Explanation in the course is very good but High improvement is needed on the basis of giving students math problems along with the teachings so that students can keep track of the course in a better way and helps in their problem-solving skills. We were given only 12 problems but we should be given more than 12 problems every week.

Great course, nice and clean presentation. Deserves the "intermediate" level. I used it to refresh my dsp knowledge from my bachelors many years ago and for this purpose the course is perfect.

I think it's quite good for one who is interested in signal processing fields and it helps you broaden your vision.

Good introduction, lots of the material seemed like review for someone who has taken signals and systems course, but it also seems like the course wouldnt really be accesible without that prerequisite knowledge. Overall, I liked the course and the emphasis on viewing signals and vectors and the vast use of linear algebra concepts.

Pro: very detailed, a lot of useful material, clear way to convey information.

Cons: lecture notes in pdf format are not available, so each time you want to recall something from the course you have to go through all the videos.

It offers rigorous introduction to DSP. Besides the lectures, it requires separate study of the materials to get well acquainted with the concepts.

It is a complex course, you should refresh your calculus knowledge before starting it. I was looking for a practical approach, the course has python notebook but I still missed practical content, with real examples and put aside formulas and analytical expressions.

needs improvement for numerical explanation.