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Learner Reviews & Feedback for Introduction to Deep Learning & Neural Networks with Keras by IBM

4.7

stars

1,894 ratings

About the Course

This course introduces deep learning and neural networks with the Keras library. In this course, you’ll be equipped with foundational knowledge and practical skills to build and evaluate deep learning models. You’ll begin this course by gaining foundational knowledge of neural networks, including forward and backpropagation, gradient descent, and activation functions. You will explore the challenges of deep network training, such as the vanishing gradient problem, and learn how to overcome them using techniques like careful activation function selection. The hands-on labs in this course allow you to build regression and classification models, dive into advanced architectures, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and autoencoders, and utilize pretrained models for enhanced performance. The course culminates in a final project where you’ll apply what you’ve learned to create a model that classifies images and generates captions. By the end of the course, you’ll be able to design, implement, and evaluate a variety of deep learning models and be prepared to take your next steps in the field of machine learning....

Top reviews

Jul 1, 2022

Excellent introduction to the mechanics of Neural Networks in general, and the Keras application specifically. Alec is an outstanding teacher, I always appreciate his knowledge and enthusiasm.

Jun 30, 2020

Such a wonderful and high tech course in the world and it is provided by ibm and coursera.Thank you ibm and coursera for such a opportunity.I'm glad and proud to be a part of this organization.

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351 - 368 of 368 Reviews for Introduction to Deep Learning & Neural Networks with Keras

By Michael G

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Apr 29, 2025

This course is supposed to have 5 modules, but I received my diploma after having achieved the first 4 modules. How come ? The video on pre-trained models alluded to much which was not explained. I believe this topic would have deserved a programming assignment.

By Tony D

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Jul 29, 2020

Very light. The current material requires much less time to finish than annoucned at the beginning of the course. The teacher could have hence taken some time to go more into details, even though it's an introduction course

By Rubel M

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Feb 12, 2022

The course should have discuss either deeplearning or keras library more deeply. As it is not discussed, at least other resources or courses should be mentioned for interesting strudent who is prone to advanced learning.

By Rogier W

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Dec 14, 2020

Course is too easy... And some guy copied my work for the final assignment after he reviewed it. IMO it should not be possible to review someone else's work, when you haven't passed the course yourself yet.

By Adaora O

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Jun 25, 2025

I feel the hands on lab should be taught and be apart of the videos in the course, I personally haven't been doing it because its all reading and not being explained, but overall the course is Good

By Pietro D

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Jan 3, 2020

The course was very elementary and brief but well organized. Week 4 (supervised and unsupervised models) is definitely too short to grasp the ideas behind the different designs.

By Somak C

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Jun 25, 2020

The topic explanations are pretty rushed for beginners. The assignment has been unnecessarily added with lots of iterations that created issues with debugging and testing.

By Dominik S

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Nov 24, 2023

Extremely simplified course of ANNs, tells you how to create a simple ANN, but you are not going to learn almost anything about how it's components work together.