Videos contain great content, are very clear and to the point. However, the malfunctioning Lab environments really took the speed (and fun) out of the course. Overall it was an interesting and valuable course.

if only financial aid was available for this course it would have been awesome, the content is pretty good, but the labs are pretty confusing as I haven't been able to figure how to register them as completed.

Es un curso muy completo que cubre muy bien los fundamentos básicos sobre machine Learning. Al final de este curso tendrás una noción de que algoritmos son útiles para cada una de las necesidades mas comunes.

Las explicaciones en los videos son bastante buenas, aunque las actividades no permiten comprender del todo lo que se debe realizar para el examen final, cuesta mucho trabajo desarrollar la última entrega.

Good Course on Machine Learning. Organization of Module content is good. The final project is simple and short but peer grading is used instead of having it automated or reviewed by a course moderator.

The course was very concise and very helpful for people who want to learn ML for a career. It would have been even better if there were some OPTIONAL readings so that we can also learn the theory part.

This course is suitable for beginners. One can get hand-on experience on creating machine learning model and basic working knowledge of some classical machine learning algorithms. Overall, good course.

A very good and informative one comes with online lab service. But the price for earning a certificate in this course is bit high that's why i'm giving it a 4 star. But the overall experience is 4.5/5.

Great course! One idea for improvement > Some of the comments in the Clustering and Recommender systems labs are hard to understand. Maybe you can rephrase / add more text to make it more intuitive.

could be split in two courses to be given enough focus. it was very condensed and needed more time and explanation in each section. The instructor was very good but more details would have been nice

Excellent course for beginners to data science field. Would have been better if the final project also included flavor of other ML methods such as Regression, Clustering or Recommender Systems.

The theoretical part is well done and very interesting, but at the end of the course the explanation regarding the use of Watson Studio for the exercise and the final test is quite misleading.

This course walks us through the fundamentals of machine learning methods. The capstone project is very useful for those who have previous knowledge of machine learning and Python programming.

I think PCA would've been a very useful clustering method to teach. AUC are a great way to measure the effectiveness of a logistic regression algorithm, it would've been useful to learn here.

Very nice course with very less time .

But i though there should be some mathematical explanation in detail what i observed there is lack of mathematical explanation.. overall course is good

That course was very instructive and provides a very good start in the field. The instructors could dive a little bit into more into technical details, or give more examples of algorithm.

its a great journey along with coursera family and very thankful of sponsering such good course.i have enjoyed alot and learning so much from you.its my pleasure to i done this course!

Great course if you have a previous knowledge in ML and python, because there's not much deepening into every subject. Useful labs to understand the coding, but with not much difficulty

Good course to introduce us to the fundamentals of ML. Some of the routines used are becoming deprecated in the notebooks, and there are quite some spelling errors within the notebooks.

The modules and in particular the Labs are good background, pay attention to the optional labs because you are going to need it to complete the final project! :) really good learning

course is a good introduction for people who know 0 about ML (like me). I highly suggest to learn a bit of Pandas, Numpy and Scikit before taking the course, it's highly advantageous.

I found that this course is very directional toward to understanding the basics of MLs techniques using python's libraries and how I can select the best choice for any phenomena.

Great content, peer review process can be a bit painful if someone has submitted a messy, hard-to-trace notebook with a lot of redundant / incorrect cells obfuscating the work.

Quite good in explanation and structured. Can be better by providing more sample study case and comment in each sample code to provide more explanation. Nice course!!! Thanks.

Good course, could have been even better if the coding part was explained in the videos. Instead, it was left to figure out yourself. Still, I appreciate the video lectures.