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too fast

decent

good

s

Great course if you know how to program, but you really need a python background to appreciate it.

quite too basics...too few practical exercise, just scratching the surface of ML

Impossible to do the exercises if you don't pay. The course is interesting.

The course should have mentioned that Python knowledge is a prerequisite.

Very nice and helpful for my next career steps.

too theoretical, not much hands on learning

Fix your week 2 lab exercise the last one

i want to see my name on this certeficate

no math exercises to practice

suggest don't include code

Oversimplified

not good

all optional labs were non function due to improper python code so useless. I also felt nothing was really taught all surface level and repeated examples. within two days I knew a middle scalar was need for optimum results which were briefly touched on at the end of week 3. the auto grader remains one of the other biggest problems. you either get 0/100 or 100/100. also, upon proper completion no feedback is given to reinforce or learn from yet, I had to trial and error and resubmit to see what the auto grader was crashing against. The last programming assignment was awful we are never even given the blueprints to do this let alone fix the auto grader despite having correct cells other data given would fail that was given. trial and error is not learning. we were expected to be flawless yet not one optional lab performed correctly due to code errors. I will use this example, I am teaching rocket science, but I leave out how the thrusters work and never talk about propulsion, would you be successful? Other lies passed off as facts you can complete this 3-course program in 10 hours a week and be done in two months how? course one i did in 9 days not 3 weeks and spent 70 hours I see course two and it's four weeks; this is not an accidental error but a grievous one. all of this is unacceptable in a paid course and supposed learning environment.

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I encountered persistent errors in Week 2 (2nd course), specifically in the exercise where I was expected to build a neural network using Keras. Despite following the instructions and trying different solutions, the autograder continued to return errors about incorrect activations and model configurations, even when the code appeared to match the expected solution. This issue blocked my progress, and I was unable to complete the assignment successfully.

Me paso lo mismo con el curso anterior y es que si no realizas los laboratorios aunque hayas aprobado todo y a pesar de que los test te dan como aprobados dicen que no apruebas y que quedas en 0%, es algo como reiterativo con coursera asi que me rindo, no continuo intentando sacarme certificados por ac谩

Awful course. Labs aren't explained clearly at all. You pay 拢37 per month and you end up with a few slides a few hours of explanation and unclear labs. The final graded assignment was a joke as well, the very first exercise was the hardest of them while the rest was trivial.

Mostly I was inundated with Nagware after ever short video segment, only to discover that Machine Learning learning was not even introduced. Wasted much time on trivialities like linear regression. I never learned anything about Machine Learning, per se.

please help in coding part , theory won't be helping building real world models, please increase lecture length and do include coding part , please otherwise it is just understanding of theory which is of no use unless implemented by ourselves

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Can't access labs even after getting full access what is the use of financial aid if you can't access all the material! If this is how it is gonna be people will probably just use torrent courses :(