difficult to follow for non coders. The language is very very technical. Waste of money.

It was a really good introduction the background on how AI works behind the scenes. I ended spending significantly more time on the class project, than on watching the video. Part of this was the learning curve with Google cloud. The option was to do the project in Excel or with Google AI. I would have loved some short instructions on how to get Vertex AI going. The instructions were for AutoML which has been retired. This class is not so much from the consumer side on how to work the various AI offerings, but more from the engineering side. I can highly recommend this class.

Truly an excellent course for those seeking a very understandable introduction to Machine Learning and the basic concepts, while still delving into the subject with practical examples. The intermediate tests were also very appropriate for measuring one’s understanding. The final test, with a sample project to complete and share in the peer review, was challenging but achievable if you studied the course material well. Learning and exploring the Google Vertex AI platform was also a great opportunity.

Awesome course! It's not too technical if you have basic math skills. The instructor speaks quite slowly, but increasing the playback speed helps. My only minor criticism is that the 6th week, when the neural networks were explained was much more difficult than all previous weeks. I wish, there were more videos explaining the training of neural networks at a slower pace and with more details.

Excellent! Instructor does a great job of simplifying concepts to make them understandable. I felt that I learned the important core concepts that are relevant to working with machine learning. The course project was challenging but not frustrating, and it greatly helped to drive home what I had learned in the course.

I love the way the course is structured. Jon Reifschneider allows you to view and download the slides before diving into the videos. He explains the content thoroughly and supports his explainations with charts and diagrams which I personally find very helpful. I'm so glad I took the time to complete this course.

Excellent course! Very well explained and summarized the key concepts. Enjoyed learning every bit. The subject matter was thorough and the project at the end put it all together. I may come back to this to keep my skills fresh. For now on to the next course in this specialization.

I rarely leave comments but this is legit one of the best courses I've taken on Coursera. It's clear enough to be accessible to beginners yet offers sufficient information to allow more-intermediate learners take assignments further. Really good, for real.

It has been an excellent learning experience throughout the program. Moreover, the "Machine Learning Foundations for Product Managers" section is beginner-friendly and easy to understand, even for those without a technical background.

This course has been a fantastic way to tool up on ML product management. The knowledge and skills I've acquired are highly relevant and I'm eager to integrate these new tools into my consulting practice and teaching experiences.

- very clear instructions

- good level of detail - general concepts illustrated with simple examples

- excellent in-video short quizzes that keep the learner focused

- good tests (clear questions and answers that make you think)

Very well made and balanced coursework. Definitely recommend this to anyone looking to break into the AI/ML space. Sets you up with a very good foundational knowledge of this vast, technical, and ever-evolving technology.

Great course for beginners to AI/ML covering a good breadth of ML techniques and models to help understand how this all works in the real world. Absolutely recommend to anyone wanting to get their feet wet in this space!

The course is informative crisp and covers the fundamentals quite decently.

If possible pls add a more detailed section on CRISP-DM process or modeling for better understanding.

Thanks ,Coursera and Duke University.

I really liked this class. It provided a good ML foundation at just the right level for me. There was enough math to communicate the concepts and principles without getting bogged down in too much detail.

Machine Learning is pretty strong and knowing the possibilities to use it is really cool. Great teacher and great content. Now I feel more prepared to talk about AI and discuss problems solution.

Good introduction to Machine Learning, which developed further with the ML course project. Overall good learning experience and continuing on with the next course in the specialisation

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As a foundation is pretty good. It can be a bit difficult the part of the algebra and the final project, but they provided instructions on how to do it. Just follow the instructions.

The course is a quick review. It would be better if there is recommended learning web links given at the end of each chapter if someone wants to know further about that concept.

The course was phenomenal. It provided me with important insights into machine learning functionality and performance. I truly enjoyed completing the final course project.

Great way to get started and introduced to concepts. Project work ensure it covers all the topics taught in the course. Great way to recap and apply concepts to play.

Sometimes I wish I had seen a simpler example or the same concept explained in two different ways. I had to resort to Gemini and Chat-Gpt to exercise some concepts.

Project at end of program was very good learning opportunity. Well done overall !! Highly recommend for non DS professionals working closely with DS projects.

The course structure is well-thought-out, beginning with a thorough introduction to the fundamental principles that form the backbone of machine learning.

Gives a solid foundation for non-experts. Especially liked the end of course project. Although a bit more of guidance tool wise could be appreciated.