Really great class overall! some of the lecture videos the speaker spoke a little too quickly but I could always rewind and rewatch.

A good course to quickly learn important aspects of ML with Python. The assignments and final exam is also very useful for learning.

quite good at the explanation and un-graded exercises.

But the knowledge could be deeper and more about parameters in Sklearn APIs.

Goodone for anyone who's a beginner in this field. But I personally suggest you to take the Data Analysis with Python course first.

Although not extremely detailed in the model optimisation part of the work, it is a very useful way to get started on applied ML.

It will be difficult for you if you do not have any previous learning or experience but at the same tie it is very benefiticial

Gives a good overview of regression and classification algorithms . It could have been expanded to other ML algorithms as well.

Great course, SO much information and great excercise, In Captone project project guidance need improve,otherwise great course

It was a hard class - the concepts made sense but it is hard to figure out how to use them without more programming examples.

Great Course to get an understanding of Machine Learning in Python with no background knowledge needed. Cheers to Learning!

Very complete course yet full of typos even in the datasets. Lots of information were redundant but an overall great value.

After taking Andrew Ng's ML course, I still learned some new things here, but this course is rather shallow in comparison.

This course was a great refresher from my data mining course in college, but I think some topics need to be expanded upon

A pretty good course to get familiar with supervised learning. Topics on unsupervised learning were moderately explained.

I learned a lot and I understood the different clustering algorithms to organize the data like DBSCAN, K-Means and more.

Good for quick overview of some of the basics of introductory Machine Learning. More focused on theory and definitions.

This course gives an introduction to machine learning by giving brief about algorightms such as KNN, Random forest etc.

I'm not a fan of their notebooks. I prefer the DataCamp model. However, the videos were easy to understand and follow.

it is all good but I cannot seem to create IBM Cloud account for some reasons... you guys have got to fix this problem

Week 6 was a bit chaotically organized. Overall, I really liked this course and would recommend it to other learners.

Course study material is excellently organized and presented in crystal clear way, which makes it easy to understand.

The content of course is good but , Add more practice material so that learner can able to applied it to real world.

Good knowledgeble course. Can me modified with simple programming tasks for people with zero programming knowledge.

A more demanding peer graded assignment would be an interesting thought for the future! :) thanking you in advance!

Nice and easy to learn for basic of machine learning.

Concept are explain in nice way with the help of good example