Kursteilnehmer-Bewertung und -Feedback für Maschinelles Lernen mit Python von IBM

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.

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 ..

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

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.

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.

E​xcellent course! The materials are incredibly well-explained, and this is a great introduction to Machine Learning. I felt motivated and felt that I 've learned a great deal.

The course structure was phenomenal . Every concept was covered very deeply yet in very simpler way. Loved the way the instructor Saeed Aghabozorghi Sir explained the concepts.

Fantastic course! Really enjoyed the videos, and the quizzes were good. The labs were absolutely amazing, can definitely use these as a good base going forward in my projects!

One of the better of the IBM courses. The videos are excellent, with the presenter doing a great job of explaining how the algorithm works rather than just what code to write.

The course was great and I think it would be better to add more lessons on visualization, on how to acquire and seek for data, and how to use other files (not only csv ones).

Excellent course who are new to the field of Machine Learning and also who are good at it , it covers basics of ML then types of ML algorithms and you also have hands on labs

The over all learning experience is really satisfying, one of the best course i have learnt from Coursera,

Thanks to Coursera !

Thanks to IBM !

For providing wonder full course

Learned a lot about several types of machine learning and ways to test the different models. Some frustration that the final project instructions were not completely clear.

Excellent course and material is covered well! One complaint is that it would be nice to know what could be expected for model accuracy so we don't try too hard to optimize.

It is a good start for ML with python. Give you a general description of each algorithm and show you the high level implementations using scikit learn in jupyter notebooks.

The final assignment was challenging in a good way. It would have been nice to have more opportunities to practice in the labs to better prepare for the assignment though.