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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

49,749 ratings

About the Course

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews


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This is the knowledge in which we will get from lots of experience only, but the andrew has shared in this course which might help us in future by saving a lot of time through this course experience


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This is a must course in the entire specialization. It covers the step by step procedure to approach and solve a problem. The case studies provided are real world problems which are so much helpful.

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151 - 175 of 5,698 Reviews for Structuring Machine Learning Projects

By Sahaj J

Aug 2, 2020

Initially, I was bored from some initial lectures. But later, I found that this is one of the most important course in the specialization because it dives to you the handful of experience in a single course which one gets after many years of practicing machine learning. At the end of this course, I am very much enlightened with the content and journey of this course.

By Amanda W

Sep 12, 2018

Loved this course as well. Presented very difficult material in a simple and easy to figure manner. Excited for more! Thank you to those who dedicate their time to making this course available, and taking the time to answer questions regarding the material. It is much appreciated and I highly recommend these courses to those who wish to learn about Deep Learning.

By Mohammed M

Nov 29, 2020

Really great course. It is very helpful to gain knowledge on the basic strategies to consider while approaching a Machine Learning problem. The assignment quizzes present you with a real-world ML problem (case study) and asks you questions on what you would do when presented with different situations. So that's a great way to get some insight on how things happen.

By Swakkhar S

Aug 4, 2020

This is a great course, unlike many other courses where you put 1/2 lines in between the code completions and pass the assignments. This one has got a number of issues where one has to be able to think about the problem and the data/model/metrics on hand to analyze and take further steps. Once again this one is from one of the top instructors of the world. thanks!


Jan 31, 2021

This course has given me insights into the importance of choosing a better ML pipeline. Not only knowledge of ML is important. We must know when and where and how to apply it our your problem. This course taught me more about that. Thanks to Coursera, if I would have taken this class in school I must have missed this gemstone information.

Thank you, professor NG.

By Ventsislav Y

Dec 22, 2018

Awesome course! I really like the explanations by Andrew Ng. This course gives you skills about how to make error analysis on your models, how to build a machine learning strategy, importance of single evaluation metric, satisficing and optimizing metrics, setting up the train/dev/test distributions and many other topics. Highly recommend this course to everyone!

By Himanshu B

Jul 6, 2018

This course is surely gona help if planning to learn deep learning.Gaining knowledge is not the best part unless you don't know how to apply the knowledge. This course is all about how and where to apply machine learning and deep learning concepts with much more practicing in real life case studies. Thanks alot for providing such a great content and case studies.

By Mukund C

Oct 14, 2019

Excellent course. I loved the "flight simulator". I found them challenging. However, some of the questions were worded confusingly, so I got the answers wrong. There is no point in trying to "trick" the test taker by confusing wording in the question as well as in the answers. But, I think this course provides a pragmatic approach to machine learning projects.

By Barbara T

Dec 25, 2018

This class was well worth the time if you've already invested some effort in learning different principles of machine learning. It causes you to reflect back on different implementations, and understand better how to set up a potential problem and determine how to improve it. The many examples helped solidify items in lectures from prior courses in my mind.

By Jagdeep S

Oct 29, 2017

This course imparts the real world experience that Andrew gained by working in the Industry on the bleeding edge of AI and Machine Learning. This class saves at least 2 years of painful learning on your own by trial and error. I think 2 weeks on this course will put you ahead by 2 years in your path of building neural networks for solving real world problems.

By Sreevishnu D

Oct 19, 2020

This specialization only gets better and better. All the courses are amazing and this course is no different. Best content and teaching as always. Thanks for having thought of ways to provide conceptual, practical and intuitive understanding of the topics and delivering it in the form of these wonderful courses.

Thanks Andrew Ng, and Coursera.

By Osdel H H

Sep 2, 2018

This course was new for me. I only had some prior knowledge about transfer learnign because I use it on my Bachelor´s Degree Thesis on image segmentation using Imagenet pre-trained weights, but all other concepts and all those guidelines of how to structure a project and how to solve the problems for make a faster and successfull iteration was really helpful

By Mohankumar S

Sep 2, 2017

Machine Learning Flight Simulator was an intriguing adventure, you get the feel of being inside the shoes of real life AI project leads! Words can't describe Andrew and team's efforts, brilliant guys! Keep up the good work :). Really excited to see what challenges you've got in store for us in the upcoming Convolutional and Recurrent Neural Networks courses.

By Tanuj D

Mar 27, 2020

This was by far one of the most challenging courses in the deep learning specialization as it covered a lot of practical ml implementation. I personally think that the ideas and the strategies discussed in the course will be highly useful while implementing real-life models. The assignments are very well designed and created a real-life scenario environment

By Deleted A

Aug 17, 2018

Andrew Ng is amazing. The way he focuses on these very often overlooked details of ML projects alone would qualify him as a professional of a different category. On top of that he has an incredible ability to explain complex things in an easy way. If he was a baseball player he would be hitting 60 HR per season while pitching 40 games with a 0.87 ERA :-)

By Rashmi N

May 19, 2019

Thanks a real bunch, Coursera for providing financial aid and bringing up this course, truly loved each and every section, coupled with quiz section at the end, is so much helpful and of course, very thoroughly made! Thanks to all the hardworking instructors and teaching assistance, and of course, coursera team for making this course so effectively! :)

By Yogi T

Mar 7, 2021

It gives an eye opener for a new learner like myself. This training brings about integrating fractions of my knowledge from my previous Data Industry. If you are new to Data-driven business, I would not recommend you to take this course. You should at least have 2 years of Data-driven business experience to understand the context of the materials.

By Sikang B

Apr 1, 2018

Generally felt this course is super useful as it helped answering several questions of "why we do things this way" rather than follow the paradigm of "it just magically works". Though there are still many magic moments while learning on ML in general, I felt this course really helped broad my view and understand the overall problem space much better.

By Luo D

Sep 14, 2017

Having finished the first three courses in the's specialization, I find this course is the most valuable one. It is not telling you the basic algorithms like the first two courses, but telling you how to ANALYZE you project as a whole in each step, and where to go next. The first two tell you how to build, this one tells how to THINK.

By Jay C

Mar 20, 2018

Excellent guide work by Andrew NG,

I really like the way he delivers the intuitions or insights from deep networks. The most important think when working with these kind of project is to look below find what you missed in considering higher level extraction. I'm really inspired by his work and keep the advice to improve performance for all projects.

By Abdelrahman R

Feb 12, 2020

Maybe its different and should help us not just thinking of Algorithms and models ,we should think out of box and think of the error from different approaches as human relative to the machine, think of the data we have, think of different distribution of the data, trying to knowing with different approaches how we should care about of these error.

By Yiyou L

Nov 13, 2017

This is a very good course. Worth taking. I am currently a data scientist and in my daily work I face a lot of data mismatch problems and I have no idea what to do after error analysis. This provides a very good guideline of how to structure our deep learning projects and what should be the thinking logics behind. Thank you Andrew I really love it.

By Nitin G

Nov 15, 2019

Have taken a formal 1 year course from a prominent Institute but these kind of concepts were never covered there. The beauty of this course and all courses by Andrew Ng is that they are so simple and easy to understand that one can't help but only understand the concepts. Best methodology and delivery of teaching I have found online. Thanks a lot.

By Nader A M

Oct 4, 2021

This course is absolutely an amazing and concise practical guide to real-world ML applications, full of examples and relatable anecdotes that Prof. Andrew has experienced himself. Highly recommended for anyone looking to work in the field or conduct projects: 2 weeks of learning this material can honestly save you months on even a single project.

By Kanwal

May 11, 2020

Excellent course and well presented material. I would like to recommend all the ML engineers to review this course before starting actual development. This course explains different intuitions and techniques with reasons what to choose, where to apply and when to apply.

Great course. Enjoyed a lot. Thanks Andrew for your precious time and efforts.