Overall the course is good. I find that the peer graded assignments are of no real significance other than to say you did it. Peers are not SMEs therefore there is no real valuable review of the assignment other than from the odd person who may be a SME. You are at the mercy of being graded by a learners impressions of what they think they learned. I didn't appreciate having to grade assignments from early 2023 - wasted time when it could have been focused on recent submissions.

content of the course is good and interesting, but finishing the peer work with creating a video is a no go. Specially for upload the video to a public cloud or video sharing platform such as YouTube. There should be also a more formal way to pass the exam, this is a content topic and not a selling or marketing course.

The three Course bundle provides the necessary theoretical material to provide an end to end Machine Learning Analytics background. The instructor has provided necessary material to produce a meaningful machine learning product management document for the Machine Learning Team for them to implement and deploy. There are small case studies and articles to support the presentations.

The Instructor provides examples from his experience why M/L Project fail due to the lack of focus on basics and details. statistics such as 87% Machine Learning Projects failed in North America, based on a 2019 study. 82% of the applications that have been contributed in the field of AI/ML have come from Universities or Academic contributions are a good indicator about the risk and focus of AI/ML field.

This course provides a very valuable and well-structured introduction to the human factors of AI, with a strong emphasis on usability, transparency, ethics, and privacy. The content is clear, relevant, and thoughtfully designed, making complex concepts accessible without oversimplification. What I particularly appreciated is the focus on real-world applications and the balance between technical understanding and practical implications. The final project was especially useful in applying concepts such as user experience design, bias mitigation, and data privacy in a concrete scenario. This course is highly relevant for professionals and educators interested in AI integration, as it goes beyond technology and addresses the human-centered challenges of AI systems. Overall, an excellent course that combines academic rigor with practical insight.

This course was practical and well-structured. I especially liked how it connected ethical AI principles (fairness, accountability, transparency) with real-world product design. The peer-graded project was very relevant and helped me build a real portfolio piece I can reuse for job applications and freelancing. The balance between theory (like bias and privacy laws) and practice (user experience design, feedback loops) made it easy to follow and apply. The course also made me more confident in evaluating ML systems from a human-centered perspective. Overall, I’d highly recommend this course to anyone who wants to understand not only the “how” but also the “why” behind AI product design.

I thoroughly enjoyed this course and learned a great deal from it. The projects and applications were engaging and helped me connect the concepts to real-world scenarios. I especially appreciated the way the material was structured and how it encouraged me to think more critically about the role of AI in business. One area I would have liked to see more of is coding and hands-on practice. While the frameworks and applications were strong, having additional opportunities to build and apply code would have made the learning even more practical and well-rounded. Overall, this was an excellent course that gave me both valuable knowledge and practical insights.

This course exceeded my expectations. As a Regional Product Manager, I found it extremely valuable because it taught me how to think about AI products from a business perspective instead of focusing only on algorithms. The frameworks for evaluating opportunities, managing ML projects, designing AI systems, and considering ethical implications are practical and directly applicable to real-world products. I was able to build a complete AI product proposal for my own company throughout the course, making the learning experience very relevant. I highly recommend it to anyone pursuing a career in AI Product Management.

I absolutely loved this course, genuinely one of my favorites in the entire specialization. The content was clear, relevant, and extremely well-designed, and I really appreciated the human-centered perspective on AI. I also enjoyed the ability to ask deeper questions and apply the concepts through the hands-on projects. The assignments were practical, thoughtful, and helped me build real confidence with the material. I highly recommend this course to anyone interested in responsible AI, transparency, and practical ML design. Huge thanks to the Duke team for putting together such a great learning experience!

The "Human Factors in AI" course deepened my understanding of user-centered design. Its practical frameworks—from emotional needs to privacy and ethics—are directly applicable to real-world AI product development. It has significantly enhanced my systemic thinking and human-centered awareness, offering invaluable insights for my design practice.

While preparing the video presentation, I was able to search and review a lot of related materials and papers. I would like to thank my colleague for checking out my project along with the professor who gave me the inspiration for the new course. We are also very grateful to the staff for their technical assistance in the peer review area.

Excellent course. It provides a clear overview of the key human factors in AI, including privacy and ethical risks, human-centered design, user trust, and successful AI product outcomes. The course is very helpful for understanding how to design AI products that are not only technically feasible, but also responsible and trusted by users.

Very meaningful. I have implemented a project that uses GenAI for generating documents. But I did not stop to consider the design approach or human factors. They came in as after the fact since I am not a trained AI Product manager. This course has been very helpful in making me think of aspects that I wouldnt have otherwise.

Great course on AI Product Management! I was genuinely impressed by the instructor’s ability to simplify complex AI concepts while tying them seamlessly into product strategy. The assignments were thought provoking and helped reinforce practical applications in real-world scenarios !

I really enjoyed watching the course, big compliments to the instructor who explained the topic in a way that really connected with me. The course sparked my interest to keep learning and developing further in AI management and machine learning. The course is perfect, 5 out of 5!

The course helped me better understand regression analysis, and model evaluation in machine learning. The instructor is very good and the presentation very clear with quality videos. I would recommend this course to all developers and project managers interested in AI.

The AI Product Manager Certification from Duke University is a masterfully structured, deeply insightful, and incredibly relevant program for any professional aspiring to bridge the gap between machine learning technologies and impactful product delivery.

This maybe the course of the specialization that is more valuable and updated even after the revolution of GenAI, the other two could be greatly improved with an update to cover all the things that happened in AI works since 2021

Excellent course. The examples, UX principles, and ethical guidance helped me understand how to design AI products responsibly. I really enjoyed the focus on transparency, uncertainty, and human-in-the-loop design.

Excellent course concept and material.Peer review grading process needs human and AI monitoring as a course completion certificate would inspire learners to register for this course in the future

Excellent Coruse and Specialization providing an effective and thorough teaching which will result being very important in my work and, more, in general, in my knowledge