Learner Reviews & Feedback for Machine Learning with Python by IBM

Presentations are very well designed. I have teaching experience and I can tell you that my style is great for illustrative purposes.

I learned to conceptually understand the mechanism and purpose of the models presented in Machine Learning. I feel like I can do things that were unthinkable for me before. Thanks IBM!

This introductory course is really very good to understand the basics as well as methods to perform activity. Would recommend highly to anyone wish to learn ML in Python. The explanation, bit of maths and code were flawless and explained well in video as well as in code (most of code is explained in sample notepad).

The information in this course is laid out in a easily digestible format that makes it possible to fully own the knowledge that you gain and put it to the test. I appreciate that the videos are straight to the point and that the jupyter notebooks illustrate varying techniques for cleaning data. Tremendous value.

Having worked my way through the IBM Data Science courses, this one was the "pay off" - it was so cool to finally apply more sophisticated techniques to real world data sets. The labs were fantastic. Highly recommend this course to anyone interested in learning about the most popular machine learning algorithms.

Complex concepts of machine learning algorithms are explained clearly with an illustration. Learner definitely have confidence in Machine learning after this course completion. A practical assignment work is really helped the learner to do the implementation of classifier model of their own and gain confidence.

This course has been awesome. I have been doing ML Work for my college for quite some time, but never understood what goes in it, and kind of surfed through the net and just did the work. But this course has given me in depth knowledge of the logic that goes behind these algorithms and for that I am very glad.

This course offers a simple and effective experience. I learnt how to find the most accurate algorithms in the scenarios. Most importantly, the Jupyter notebooks provided are although optional, but you should study them thoroughly. They might seem difficult on an overview, but are very easy to understand.

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.

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.

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.

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.

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.