This specialization is intended for data scientists and software developers to create software that uses commonly available hardware. Students will be introduced to CUDA and libraries that allow for performing numerous computations in parallel and rapidly. Applications for these skills are machine learning, image/audio signal processing, and data processing.
Very slow pace but otherwise a great learning opportunity, especially the lab resources
An experience I never had before and knowledge I never had before both came through this course. Thank you, Coursera!
Very helpful. Learned something basic that was very important. Many thanks!
I good course that gives you hands on experience with cuda GPU programming. You have a VS code desktop in the browser with a LINUX terminal. LInux machine is connected to a nvidia A10 GPU. very cool.
Clearly provided material with labs and quizzes that are well organized.
I think it is fantastic, I would like to offer my gratitude to the author of this course even though I haven't yet finished it all.
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The instructor is explaining in a voice and manner that puts you to sleep easily.
The course materials are not well-prepared. As a student without prior knowledge of GPU programming, I find it very hard to follow. Also, the instructions of assignment are confusing and unclear, I even couldn't know what I should do. I tried to find tips from discussion forum, but I realized that lots of students' questions there didn't receive any response from TA or staff .
Overall, this course makes me frustrated and isn't worth to me to continue my subscription anymore.
Assignments really need to be worked on. There are so many errors and the overall objective of the assignments in not clear. Instead of working on the concepts, I had to work on how to run files in the assignment.
The theory and explanations provided is also not adequate.
Lectures are terrible: no real explanation of what is going on, just definition of terms. Some links to reference material are broken. Presenter's voice is not very clear: speaks in low vocal fry (i.e. mostly whispered). Example code in labs have minimal explanation. The examples are not explained in lectures. This is stuff we'd expect just from a brief Google search.
More about concepts of threading, but not about gpu\cuda programming. It's ok, but if you are familiar with these concepts you could skip this course
Labs sometimes have some little bugs, but could be resolved easily based on hints from corresponding discussion section
Very slow pace but otherwise a great learning opportunity, especially the lab resources
Very helpful. Learned something basic that was very important. Many thanks!
Clearly provided material with labs and quizzes that are well organized.
Great introductory course, well paced.
Great Course
GOOD
good
good
Zoʻr
GOOD
Overal a good class, very useful introduction to CUDA including lots of key information - It would be very beneficial to have some more information and examples on the parallel classes, mutexes, atomics, asyncio etc. - Some of the existing, provided code in the assignments can be a bit confusing because it seems as if the assignment is expecting more than is required. There were a few comments about this in the forums I think
I learnt a lot, and exactly the stuff I wanted to learn + some things that were unknown unknowns to me.
Would give 5 stars, but I think it's missing a bit of a polish, some exercises are not as clearly stated as they could be, and there are links to additional resources that are still broken. I think it is still worth doing the course despite all this, but I would like to see the course administration improve these things.
Super low energy presentation, and the material seems largely cut and paste from NVIDIA and other online sources, which I already can find and organize quickly using ChatGPT. This first course was "ok", but didn't really add much momentum to my learning.
The teaching is good, but there are quite a few mistakes in the task instructions, especially in the last ones. Please remember that we are students, and any mistake you make can confuse us and slow down our learning.
good course to boost your skills