It's okay for intro but I feel need in more practice. Don't expect to get skills from this course. You will get a lot of new theoretical information with just a scratch of practice. So I suggest to mix this course with some good books + practice.

it was a really great theorical course but the practical parts were too small. so I know alot about the concepts and I can calculate stuff but i can not implement them that much , and I'd rather the course to have more difiicult math! well done!

it good but missing small exercice to practice more, with little question.. like "what is Array ?", "what mean lambda ?" basic stuff when we arrive in the TP.. we are not ready and need to re watch video during the TP.. that my point of view..

I reported a technical problem with a graded practice quiz, 'Gradient descent for logistic regression, ' multiple times without any response from Coursera; the question doesn't appear. Now, I have completed 99% and cannot move forward! !!

It is really interesting, I think I have miss more focus on connecting everything together from the function f_wb to cost function to deltas to preditions. The labs are not very challenging.

Code cannot be transferred easily to jupyter notebooks or google colab. The course was 90% theory. Needs more real-world practice and projects. Other than that Theory was very good.

the course is well structured and you'll gain the fundamentals of ML. But the practical labs should be more challenging in my opinion. I am looking forward to the next course.

There is very less practice content for students. I hope keeping more graded notebooks would be helpful for students to get more practice and understand the concepts better.

The course is interesting but focuses on very theoretical aspects, more suited to academia than the working world. Unfortunately, the audio is not the best.

This course requires Python programming experience using the libraries this course needs. It is not suitable for learners with basic coding experience.

Much more of the lesson content needs to be focused on the code, rather than the underlying maths, seeing as it is purely code which is assessed.

Love the trainer. Would have been nice to start coding earlier. By the time we were called to actually write code, it was way too late.

The videos were really helpful, but the optional labs were useless. Besides, the practice labs felt like you are jumping few steps.

Doesn't really enable "DeepUnderstanding" - all abit rushed. Spend time afterwards going through more examples with more rigor.

course is well structured, still if u want to learn and practice the labs, u need good python skills, but for knowledge its best

I just started today. i wanted to try if i can access other week context. why is it showing week 3? i am confused.

Had problems with Python. I does so much for you it sometimes makes it difficult for a C, C++ or Java programer

Lectures were very clear and smoothly explained but the discussed consepts were only for complete begginers.

Thank you sir . I learned many new things from this course which will help me to much in my research work..

It's a good program, but unfortunately you can't get the certificate while it's in the free trial version.

Good for absolute beginners with no background. Too slow and peace-meal information for anyone else.

The explanation of the theory is good, but there is no explanation at all when it comes to coding

looking for online coarsens for cnc operating my own I am in country 2 hrs from edmonton ab.

Lot of great learning, but not taking into account using a lot of newer open source options.

Everything mostly taught was theory.I learnt very few concepts of coding.Disappointed!!