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Learner Reviews & Feedback for Introduction to Machine Learning by Duke University

3,249 ratings

About the Course

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with PyTorch, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more)....

Top reviews


Aug 4, 2020

I felt that I took the best descition in taking this course, because the professors took this course with atmost clarity and made even the difficult concepts understand easily.

Thank you Professors


Nov 26, 2020

Thanks Coursera and Duke University for this course. It is very insightful to get understood the basics of ML and applied ML in numerous fields. It really made me to move ahead with ML domain.

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1 - 25 of 760 Reviews for Introduction to Machine Learning

By Kartik G

Oct 29, 2019

Although the course is great from a theoretical point of view, but it has two major flaws. First, it doesn't provide the fundamentals of Machine Learning but instead directly moves to Deep Learning, although building those concepts from ground up. Also, from a practical point of view, this course is really lacking as there is not a single explanation video on any of the coding aspect of Deep Learning and the videos that even exist just ask us to read through the Documentation to learn the practical aspect.

By Lewis C L

Apr 22, 2019

Much weaker than Stanford offerings. Strange buildup of topics for a breezy, but not particular accurate understanding. For example: multiple layers of a neural network is introduced before multiple category classification. Transfer learning is introduced incorrectly. The matrix representation of multiple features of an example with multiple examples is introduced very late in the course. The instructor is conscientious and seemingly knows the material despite using non-standard terminology. One wonders if he is primarily a teacher/researcher and rarely a practitioner. One wonders if Duke is a leader in machine learning research.

By Casper v d V

Jan 1, 2021

The course is okay, the teaching is helpful explaining the concepts of machine learning well. The problem is the connections between theory and practice. The assignments in pytorch are completely decoupled from the course materials and not explained very well. They expect you to code a model directly from mathematical theory with poor explanation of the pytorch framework and syntax.

By Vishesh S

Apr 25, 2021

This is very wrong thing that happen to us.Coursera tolds that this course if free due to our 9th birthday celebration.But when the time of claiming certificate .Its shows us to buy a certificate.This is cheating .I hate this app ..

By Preethi C

May 26, 2020

It's really an amazing field to learn new things and from institute is like Amazing to me I've learnt more's not at all boring and we'll will be excited for future experience with you 💯

By Guido C

Jul 9, 2019

Very good introductory course, I highly recommend it to anyone looking to get a flavour of the methods behind the recent advances in AI without going into super-technical details.

By Michael B

Sep 30, 2018

Excellent course. Concepts such as gradient descent and convolutions as they pertain to neural networks are explained without going into the mathematical details but, in my opinion, are explained more intuitively and better, as compared to most other courses. The course does include some ungraded Jupyter notebooks exemplifying key elements of deep learning networks. Highly recommended to 'cement' understanding of neural networks.

By K S S

Aug 5, 2020

I felt that I took the best descition in taking this course, because the professors took this course with atmost clarity and made even the difficult concepts understand easily.

Thank you Professors

By Nagendhiran

Nov 27, 2020

Thanks Coursera and Duke University for this course. It is very insightful to get understood the basics of ML and applied ML in numerous fields. It really made me to move ahead with ML domain.

By Abhinav t

Jul 3, 2020

A very concise and yet beautifully constructed course for introduction to machine learning for absolute beginner having basic knowledge of probability and mathematics.

By Sonic S P

Mar 31, 2020

Very good introductory course ,very well designed and professors explaination is very easy to understand .Go for it guys !

Happy learning !!!!

Sonic Somanna PK

By Erica R

Oct 5, 2018

This was a really great course for understanding the basics of machine learning through a lot of simple but relevant, real world examples.

By Shukshin I

Nov 24, 2018

It was great to touch new professional area and to understand its fundamentals. The course gives a broad view on machine learning, so I think now I really understand, what the machine learning is and how to use it in my work and even my political investigations.

By Jonah P

Jun 2, 2019

The course is a good balance between learning key concepts and doing coding, the coding being optional. The phrasing of quiz questions and answers were sometimes confusing.

By Eric T

May 28, 2019

Great course ! Pr Carin is clear enough to make you understand complex concepts like LSTM. The Math, calculus, algenra and prob are not too difficult. I enjoyed to follow this course ! To conclude a good introduction to ML to make you go deeper into the subject

By Fuzail A R

Sep 2, 2020

A beginner like me who wanted to learn and expirement with machine learning but didn't know where to start, well this is the best course for you. The learning process is highly engaging and the concepts are explained in a well-refined manner.

By Jeff M

Jun 29, 2020

I thought this was a great course to build up an intuitive understanding of a few different machine learning techniques. It is certainly skewed more towards breadth than depth, but this is unavoidable given the short length of the course.

By Manoj k K

May 19, 2021

The course covers all the topic's regarding the machine learning and has an excellent explanation of concepts and the slides are very easy to understand thank you for such a wonderful course !

By Sai C

Apr 17, 2021

The concept is explained in a great way but i didn't understood even a single part of programming part as no one explained that

By Umme A

May 8, 2020

Too tough

By Reza M

Jul 30, 2021

This is a very good introduction to machine learning topics. From history to implementation of the concepts in different fields of machine learning, it helps developing a good sense about machine learning. As somebody with no knowledge before this course, it helped me a lot to understand machine learning and the areas that I possibly like the most.

By Abdul M

Apr 2, 2019

I have a background in pathology and I wanted to understand how machine learning works so that I can take an active part in the changes within my field and understand what is happening. This course was an amazing experience of learning, for someone like me with no background in calculus or linear algebra.

By Prajwal K

Apr 26, 2021

Just learning the course and loved it coz of its depth in knowledge in Machine Learning.

Week 1 covers almost all fundamentals topics and lays the solid foundation to the learner in ML.

Looking forward to enjoy learning this course attentively, complete the assignments.

By Fahad K

Jan 25, 2021

I suggest to every who is interesting in online course , should study with

They will teach you in a such that all your doubts will be cleared.

They have quiz and assignment at the end of lecture.

So I strongly recommend this to every one.


Aug 9, 2020

The concepts presented are very clear. I understand a little more about machine learning thanks to the course. The support of the concepts using PyTorch was also an interesting aspect in terms of integrating theory and practice.