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Learner Reviews & Feedback for Basic Artificial Neural Networks in Python by Coursera Project Network

109 ratings
16 reviews

About the Course

In this 1-hour long project-based course, you will learn basic principles of how Artificial Neural Networks (ANNs) work, and how this can be implemented in Python. Together, we will explore basic Python implementations of feed-forward propagation, back propagation using gradient descent, sigmoidal activation functions, and epoch training, all in the context of building a basic ANN from scratch. All of this will be done on Ubuntu Linux, but can be accomplished using any Python I.D.E. on any operating system. We will be using the IDLE development environment to write a single script to code our simple ANN. We will avoid using advanced frameworks such as Tensorflow or Pytorch, for educational purposes. Note that the resulting ANN we build will be use-case agnostic and be provided with dummy inputs. Hence, while the ANN we build and train today may appear to be a useless demonstration, it can easily be adapted to any type of use case if given proper, meaningful inputs. I would encourage learners to experiment- How easy is it to add more layers without using frameworks like Tensorflow? What if we add more nodes? What limitations do we come across? The learner is highly encouraged to experiment beyond the scope of the course. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

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1 - 15 of 15 Reviews for Basic Artificial Neural Networks in Python

By llwen

Jul 19, 2020

the python code written by the teacher is not quite right and has several errors, I don't knonw how he got the result in his computer.

By Erwin

Jul 22, 2020

This is not correct to charge 10 dollars for a course like this. There are python libraries used (e.g. for creating the dataset) without any explanation. There are derivatives of a sigmoid function and the only explanation was "use of the chain rule of derivatives", but this is not explaining how one can get from the initial function to the derivative. And this is only an example of the things not well explained. There are some good things in the course (like typing everything in on-the-fly and explaining what to do), but the hardest part (like implementing the backwards propagation) goes really fast. I think too much time for the easy part and too fast on the most difficult part. I'm not saying that this course should be for free, but 10 dollars is too much for this content. There are courses on the same topic for free that are coming close to this one. I expected more quality screening from Coursera (although I had some other courses from Coursera that were really ok).

By Naman J

Sep 03, 2020

Very Low level project,

Gives a very bad intuition and not Worth the Money

By Deise O

Aug 15, 2020

Finalizei o curso, mas achei que foi muito curto.

By D V N A

Jul 21, 2020

It is an excellent project and is an amazing way of testing the old concepts and applying them in a new way.

By Charles I N I

Sep 14, 2020

Basic explanations for beginners

By Ashwin K

Aug 31, 2020

A great project

By Carlos M C F

Aug 26, 2020

thank you

By Aracatla s

Aug 14, 2020

Very good

By Abubakar H

Jul 25, 2020


By Gaurav G

Jul 01, 2020


By Mr. S W

Aug 13, 2020


By Prasanth k k

Aug 16, 2020



Jul 31, 2020


By Gaureesh C

Sep 03, 2020

The Virtual machine reloads quite often which gets very irritating, the project is great besides that.