Great course.

It could be even better if programming assignment were provided in each week but still, final assignment was of great quality and I found it really engaging. The program introduces you to scikit learn which is again a wonderful advantage of taking this program. I am giving this course 5/5.

A very good course for beginners. It's quite practical and helpful. If it can go to more details of the machine learning modeling algorithms, it would be better. I get an overall picture of simple machine learning tasks but cannot handle real work task yet. The real world is much more complicated.

This is an excellent course. The teacher explains very clearly and in the shortest possible time, I have gained a solid understanding of the core concepts and practical applications of various algorithms. I highly recommend it for business students who want to get started with machine learning.

The course was quite challenging. I especially appreciate how the labs required significant modification and deep understanding of the underlying motivation for the code in order to complete the final project for the course. Thanks to the lab authors and instructors for some high-quality demos!

The course was thorough and a great introduction to machine learning. The capstone project was challenging and required me to have a good working knowledge of the various models. This has been the most intensive course, so far (course 8 of 9), in the IBM Data Science Professional Certificate.

The course is really good for machine learning beginners. I would recommend everyone to take this course as it gives you all the basic knowledge and working of ML. It is fun to do with the Jupyter notebook tool which gives a great actual experience. Thanks a lot. This course helped me a lot.

It is indeed a very thorough course, yet easy to understand. The animations and visual graphics made it an engaging and pleasurable experience. Learning classification, clustering and regression was made easy in such a way, that I could do it all over again without hesitation. Keep it up!

BEWARE : student access to ibm cloud for last project lab is limited : I have reached the max usage working 10 days for 2 hours. I would prefer have been warned at the begining of the course about this limitation instead of discover it at the end when I needed to finish my last project

I really loved doing this course and I definitely recommend it to anyone with a minimum level of machine learning algorithms who is looking to gain a better and more comprehensive understanding of this subjects. The instructors are awesome, as well as the course materials and videos.

I think it would be beneficial to talk about neural networks somewhere after the gradient of steepest descent section. I did appreciate the course talked about many other ML algorithms that are not typically covered by other programs - and the lab notebooks are extremely valuable.

I suggest this course to others because of good teaching videos and the top of that,coding enviroment just like that google Colab and Kaggle with simple and substantial explanation in comments. It is really amazing .Thank you to IBM team and coursera website . best wish for you.

If more knowledge on 1) how to find the optimal depth value for decision trees and variables for other models; 2) explanations on parameters used, will be elaborated in hands-on lab notebooks, it would be better. Those are important to new beginners with zero idea on ml models.

It is one of the best introduction course to Machine Learning.

The material is well explained to someone with a beginner level of understanding to Statistics and Machine Learning.

All the material is presented in a way that is easy to understand, without leaving out the details.

One of the best course on Coursera so far. Instructors not only covered the theoretical side of the the course but also taught us how to implement various algorithms practically. I would definitely refer it to anyone who wants to start a career in the machine learning field.

This course is a good chance to start python programming and reviewing ML concepts with deeper insights. I would suggest it for those who are familiar with ML and its algorithms. For those ones who want to start learning ML, it is better to take ML courses with Basic level.

This course is great. Not only does it cover the main theories, but it also provides a full practical codes from instructors. The end-chapter quiz is well structured also, to deliver a complete check of the ML principles you have learned throughout the course. Thanks, IBM.

It was a great experience for me to start learning on Coursera with this course. I face with great tools, great learning methods, so I became interested in getting other courses of IBM in this field. thank you, Coursera, thank you, IBM and thank you dear Saeed Aghabozorgi.

Great course, cover many important aspects of classical machine learning algorithms. The lectures are very focused and not tedious. Labs are excellent, and can serve as a starting point for every data science project in the future. I definitely recommend taking the course.

This is one of the finest courses for anyone who wishes to transform his/her career into Machine Learning. It has optional external tool assignments after each chapter to help you understand and try out code and the concept. I would highly recommend this course to anyone.

Hello Dears,

This course was very great for me because it taught me a lot of practical projects.

I would like to express my special thanks to everyone who built the coursera site and teaches these courses and IBM company.

Thank you so much,

Kind regards,

Mohadeseh Emamipour

If you put your heart to it, there is really a lot to learn in the course. The course touches quite some ML topics and gives a good introduction to it. I feel I got a whole new set of tools to use, and i am hungry to learn and experiment more.

Really enjoyed the course!

The videos and labs were remarkable in that it was able to concisely communicated vast and complex information.

I did have to do additional research to fully understand and appreciate the material because I am not coming from a programming or statistical background.

Great course.

Knowledge wise, just like Prof. Ng's, minus the mathematics foundation.

Practical wise, carefully designed labs really help learners understand the data cleaning processes, understanding data through visualization, ML algorithms and evaluation metrics.

The course was really great. You have the luxury to explore in-demand practical skills and apply them in fun ways. ML is applicable to the industries, and our lives. I've been blessed greatly by the expertise of the instructors to design a well-structured content.

It's a very precise and practical course. It focuses on the main ideas and application aspects of M.L., without drilling too deep into the math rationale behind.

To get the most from this course, it's good to equip yourself with basic knowledge in numpy and pandas.