One of the best course I have come across. Every module was brilliant and taught so well. Thanks to coursera and IBM for such a lovely course. Special thanks to all the tutors and mentors.

This course provided a solid platform for machine learning and I have thoroughly enjoyed every second of it. No regrets and I look forward to continuing with similar courses in the future.

A great course for people who have PYTHON skills and want to move toward data science. I recommend this course, however I suggest that you take a PYTHON course before taking this course.

I Learned basic algorithms, error evaluation, analysis on various datasets. At the end of the course, I am confident to apply my knowledge to solve problems with the required algorithms.

well designed course... smooth. it is for beginners, gives a good basic grasp.. the exercises are the best, pretty painless to get up and running, easy to experiment (highly encourage)..

I have learned the basic concepts of different machine learning algorithms. Understood how to build a model using different dataset and how to predict and found out the insights of data.

Very interesting course, the final assignment is very good - it's a challenge, but it's covered in the course so one doesn't need to take another coursera course to pass it successfully.

It is a well - designed course for understanding the ML fundamentals. It teaches you the main concepts and the lab notebooks are really supportive to try on the algorithms with pythons.

Good for data scientist who wanted to explore more in different classification algorithms along with evaluation matrix while developing the machine Learning Models or Predictive Models.

Could you classify the users based on their demographics and educational standards and predict the rating they would provide :). I will love to see the results or help write the code ..

That is the wonderful journey to learn about the supervised and unsupervised models. Moreover, there were the plenty of labs, which help me to practice a lot. And to have a firm grip.

The lecture videos are minimal and also defines the machine algorithms without ambiguity.

The hands-on project was interesting to apply Classification algorithms on Jupyter Notebook.

It was an excellent course for beginners. However, I just like to add one thing here, please take mandatory comments from the reviewer why the deduction in the points they are doing.

This is one of the more challenging courses. You need to pay attention and review the material. The project will require some additional thought beyond just parroting the material

I enjoyed this course. The talks are very well structured and clearly define outcomes and tasks. I also enjoyed the explanation of the mathematical content and the practical used.

It is good to learn this course and it help me in term of analysis and predicting by using some machine learning . It is very comfortable to my time so I can learn when I am free.

Good and broad explanation of popular machine learning algorithms. The mathematical side of each algorithm should be learned outside of the course for more in-depth understanding.

Very useful course to kick start machine learning. It helped me to understand the basics along with coding part of machine learning clearly. I recommend this course for beginners.

I'm so delighted to have this lesson with Coursera. The instructor could explain the material clearly. Then we can keep the video to review it again and again. Thank you so much.

Tons of information in just one course. I really like it, but it would be great if there are further courses from IBM to further deepen the knowledge acquired during this course.

A rewarding experience because I have been able to learn very valuable information. It is an excellent course. It has helped me in the personal and professional field. Thank you.

Your explanations are clear and left many students happy, though you could provide a link to the extra learning materials of algorithms to have a similar reference of knowledge.

Excellent course for someone who needs to get a breif of ML and start implementing it. Significant information provided in short span of time in very crisp and efficient manner.

A good introduction to basic ML algorithms, but does not cover deep learning models (there are other courses for this). Assumes a reasonable amount of familiarity with Python.

This course is a great starter for those who want to learn the basics of Machine Learning and also gain experience on Python ML libraries by using them with real-life examples.