VB
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This is a very good course for people who want to get started with neural networks. Andrew did a great job explaining the math behind the scenes. Assignments are well-designed too. Highly recommended.
SV
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Nothing can get better than this course from Professor Andrew Ng. A must for every Data science enthusiast. Gets you up to speed right from the fundamentals. Thanks a lot for Prof Andrew and his team.
By Jimmy S
•Jul 8, 2020
Andrew does it again. This course was super fun to take. I feel I have more intuition on deep neural networks than before.
By Prem P
•Jun 23, 2020
Really an amazing course, has helped me a to understand the bare-bones of the deep learning. Thank you for amazing course.
By Poduri S L S
•Jun 19, 2020
If the lecture notes is available in single doccument , it will be easy to go through. Overall a great learning experience
By Nitishkumar H
•Jun 16, 2020
I have learnt lot concepts from this course. It cleared lot of doubts in understanding mathematics behind neural networks.
By Hadiqa A
•Jun 13, 2020
I learned a lot of new things, that was really helping for me to explore new things. I Want to learn more related courses.
By Ivan G K
•May 18, 2020
Great introduction to deep neural nets. Instructor provides a good intuitive understanding for the inner workings of ANNs.
By Gabriela M
•May 11, 2020
The course is really good. The videos are clear, very well explained and the practical activities are perfectly organized!
By anugya s
•Apr 25, 2020
I loved how the whole implementation was from scratch not using libraries. Now I will remember the hidden concepts always.
By ViswaTej Y
•Apr 22, 2020
Excellent way of explaining, having everything beautifully organised and making it highly interesting for all the students
By Simon D
•Apr 13, 2020
Intuitive and applicative way to implement Neural Networks. You really get to undertsand the mechanics behind building NN.
By Akshay V
•Mar 29, 2020
Great Course! I learned a lot about vectorization,broadcasting, neural networks basics etc. Thanks Andrew Ng and Coursera.
By Mehl C (
•Mar 25, 2020
Amazing teaching by Prof Ng. I strongly recommend this MOOC for anyone interested in acquiring knowledge on Deep Learning.
By Stefan W
•Jan 27, 2020
Great Course! Only the programming assignments could maybe be a bit more challenging, i.e. especially less pre-structured.
By Filippo L
•Jan 4, 2020
Great Course, gives useful insights on Neural Networks and guides along the way to develop algorithms for computer vision.
By Mansoor R K
•Nov 28, 2019
One of the most in-depth courses for Deep Learning. Highly recommended for anyone looking to begin a career in this field.
By Marcus V C A
•Nov 19, 2019
It's a very good course. I think it give us some insights and some mathematical background to go deep in deep learning! :)
By jiangjingwen
•Nov 13, 2019
I have learned the basic knowledge of the Neural Networks and Deep Learning.
I will recommend this course to my classmates.
By yegna s
•Aug 9, 2019
Just follow the course and it will walk you through all the concepts from rudiments and provide you the necessary insight.
By Gajula J
•Apr 7, 2019
Best course for getting started with deep learning on internet. Thank you coursera and teachers for creating the best one.
By Muhammad H M
•Apr 2, 2019
One of the best course out there on getting started with all the basic stuff related to Neural Networks and Deep Learning.
By Deleted A
•Feb 26, 2019
essential for Neural Networks and Deep Learning learners.
if you want to know how to make models you must listen this class
By Cajetan R
•Jan 15, 2019
Andrew Ng's course is best to give a kick start to your career in ML and Deep Learning .
He makes your fundamentals right!
By divya p p
•Jan 12, 2019
very clear explanation of concepts and well managed assignments. gives confidence on building multi layer neural networks.
By Hassan K
•Dec 16, 2018
I wish I had access to the Assignments and Quizzes as a free user even if they aren't graded.
BEST COURSE EVER. THANK YOU.
By Rounak P
•Aug 16, 2018
This course goes to great lengths the explaining both the intrusion as well as mathematical background of neural networks.