Excellent course. I really enjoyed being confronted with real life deep learning problems and hoe to go about structuring the project. The "flight simulators" were really beneficial for my learning experience.

Great course with insight into how to prepare your ML and DL projects and the order of operations and caveats and considerations to take into account with your data in real-world scenarios. Highly enjoyed it!

Excellent, very valuable to have advice on how to troubleshoot and make progress with a project. ML is not just about equations and code, and this distilled wisdom will help me get started as an ML researcher.

This course offers great insights on building a ML project, which are also applicable in different types of projects in real world. Also, this is truly distinguish from other deep-learning courses on internet.

Learned about how we should manage our DL project and what to priotize first, these are something one learns after he has gone through such problem, so it was nice to learn about it beforehand from the expert

I thought this course was very helpful in analyzing neural networks. While I did enjoy the quizzes, I wish there were more to test my knowledge on whether it is more quizzes or actual programming assignments.

Very practical, simple short course!

Very good materials that can generalise how to build a good ML model.

Very handful exercise

Nice interview from experts

This is a MUST TRY course, because it's too BEAUTIFUL!

This course was great! This course details various strategies behind creating a machine learning project, as well as the theory behind those strategies. This course is a great mix of practicality and theory!

The most informative course that i have ever encountered in this field. I am training deep learning algorithm for my thesis, after taking this course I am able to do a lot of things that improved my network.

It was very useful for me to learn about posible sources of error when deploying a machine learning model, and how to fix them as well as improve it with artificial synthesis or transfer learning techniques.

As a college graduate who took ML classes in college, this course is a lot more useful in terms of developing an intuition toward iterating on ML projects. The interview with Karpathy is the cherry on top :)

This was truly amazing! I mean an entire course on the subtleties of gaining skills that we can actually apply in real life is really needed. I am super glad I took this course! Special Thanks to Andrew Ng!

This is a quite different class. It's less math, less formulas but there is so much to learn from the experience of Professor Ng, a whole lot of best practices to follow and tricks to learn. Great contents!

Great and unique course! I think that such topics should be a part of any professional ML course.

Having said that, it would be appreciated if the sound volume had higher expected value and lower variance :)

This course gives me an overview sight of the whole process of machine learning project. Not only I know about the technical things, but also know how to structure and point out the position of the project.

A lot of good thoughts on working with models. I think just getting your hands dirty with some models would help as well. :-) Would be interesting to set up a model to do some difficult tuning exercises.

This course gives you an experience, which otherwise you'd take tens of years to garner. The simplicity with which Andrew explains the challenges is commendable as well. Thank you for teaching this course.

It is a really good course to build your intuitions and decision making capability for your machine learning projects, I really like the way Sir Andrew Ng relates all the concepts with real world examples.

Un curso que no se encuentra en ningún sitio. Necesario para estructurar proyectos (en todos sitios te enseñan a hacer modelos pero en pocos te enseñan a estructurarlo bien y a saber cómo y en qué mejorar)

Some glitches in the videos, but the content is great. Andrew is an awesome teacher and these are really unique tips coming from his vast experience, it is hard to find similar content elsewhere on the web

The discussions on practical guides about designing deep learning systems, dealing with data, bias variance trade-off, and how to organize projects to optimize time usage are much needed for practitioners.

Practical advice for new students when tackling a real-world ML project and how to approach to optimize a model's performance. The quizzes provide good examples of use-case scenarios and decisions to take.

I think the simulations were great. They give an excellent approach to real life enterprise scenarios where you have to take important decisions. Great compliment for the first two courses of the program.

Step by Step approach to structure Your Machine leaning project from scratch. The cherry on the cake is simulation quit provided at the end, helps quite fast to get the practical approach to the problems.

This course is very helpful to fine tune our machine learning and our deep learning projects and probably more input to the different types of transfer learning examples could have been much more helpful