Feel strongly, that this is the best of the 3 core courses in the specialization. The lectures were excellent and the notebook modules supplemented the lectures very well.

This is a very first course of Machine Learning that I have ever completed. I believe, this is a very good course to understand some basic applications of ML in real life.

Really good course. The instructor taught in a very precise way. The teachings were spot on and comprehensive. After this, now I can start to work on real-life projects.

I enjoyed this course it was fun and very informative. This course also gave me a bunch of resources such as The Elements of Statistical Learning which is a great book!

ML is a wonderful course.I learn new concepts with hands on experience.Each and every algorithm concept is clearly explained .I learn how to handle real time data set.

It's a best course for the one who wants to learn machine learning with python. All you need to do hard work for the certification. Give your best and crack the codes.

Liked the course! At times a bit challenging but the discussion forums are helpful. Gave me a good overview of the topic, but I feel I have just scratched the surface!

Well designed course. The last assignment really makes you review every lesson learned in previous modules. I recommend this course for intermediate python developers

It's very hard to teach ML in such short course. But this course did very well, focus on how to use sci-kit classifier from clean data to select model. Very practice.

This course has been really helpful to me! All the contents we need to grasp each week were well-designed and the assignments are easy, interesting and enlightening.

The course is overwhelmingly interesting and provides readily available tools. The teaching assistants and professor are all extremely helpful. Absolutely suggested!

Very excellent course. Well done explanations even if there is some language confusion. Taking the time to really understand the concepts makes all the difference.

Inspirational course, learning you in a comprehensive manner, a thorough approach to machine learning with the target specific peculiarities and possible pitfalls.

A course that gives not only solid understanding of Machine Learning, but provides with skills to actually practice it on real world datasets. Highly recommended.

I like how the many different ML algorithms are explained in such a high-level. This is a good anti-dote to more theoretical courses. Best MOOC I have done so far.

Fantastic, and challenging course, a must and recommended. For those who are interested in Machine Learning and have experience with Pandas and Python programming.

Great course, with clear explanations. It is a great introductory course. As the name implied, this is for applying the tools needed for Machine Learning practice

It was really great and improved my knowledge of machine learning algorithms. However the assignment were so diffrent from what have been teached in the courses.

A very good course that I would recommend for others to take. It covers quite a bit of material but it is still worth it. Very satisfied with what I learned.

The evaluation is sometimes problematic, otherwise is very good. I had a problem with matplotlib which was just imported and nowhere was written to remove it.

really great course, using online jupyter notebook is a great way to increase hands on experience. auto-grader needs some improvements but not a huge problem

I learn many new things which I have not learn in my university.The best quality courses encourage me to learn and explore more in deep Machine learning.

excellent course. Lectures were good, not too heavy on theory, and assignments were challenging but doable. I liked assignments much better than the quizzes

Great course. The material is well thought, the assignments are excellent. I learned a lot and I am already leveraging what I learned in the course at work.

Perfect course! No math, only applications, definitely I will use it later in my studies since course provides many useful examples / explanations / codes.