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Deep Learning with Keras and Tensorflow

Deep learning is revolutionizing many fields, including computer vision, natural language processing, and robotics. In addition, Keras, a high-level neural networks API written in Python, has become an essential part of TensorFlow, making deep learning accessible and straightforward. Mastering these techniques will open many opportunities in research and industry. You will learn to create custom layers and models in Keras and integrate Keras with TensorFlow 2.x for enhanced functionality. You will develop advanced convolutional neural networks (CNNs) using Keras. You will also build transformer models for sequential data and time series using TensorFlow with Keras. The course also covers the principles of unsupervised learning in Keras and TensorFlow for model optimization and custom training loops. Finally, you will develop and train deep Q-networks (DQNs) with Keras for reinforcement learning tasks (an overview of Generative Modeling and Reinforcement Learning is provided). You will be able to practice the concepts learned using hands-on labs in each lesson. A culminating final project in the last module will provide you an opportunity to apply your knowledge to build a Classification Model using transfer learning. This course is suitable for all aspiring AI engineers who want to learn TensorFlow and Keras. It requires a working knowledge of Python programming and basic mathematical concepts such as gradients and matrices, as well as fundamentals of Deep Learning using Keras.

Status: Generative AI

Status: Generative Model Architectures

IntermediateCourse23 hours

Featured reviews

4.0

Reviewed Jul 25, 2020

Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.

5.0

Reviewed Jul 28, 2023

This course had a best and fast pace understanding for ANN, DNN, RDM and Autoencoders with Tensorflow

5.0

Reviewed Mar 25, 2022

The detail of prsenetation is awsome and make learning interesting. Thank you Corseara, Thank you IBM

5.0

Reviewed Jul 2, 2020

Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!

5.0

Reviewed May 18, 2020

Excellent course to get started with tensorflow and deep learning.Really enjoyed the course.

4.0

Reviewed Jan 4, 2020

Very clear explanation and well organized course. I give 4 stars because videos of Week 5 are missing the audio and subtitles.

5.0

Reviewed Aug 16, 2025

Thank you very much for the great organization and the depth of the materials presented.

4.0

Reviewed May 17, 2020

It would have been nice if the video tutorials would explain the code section as well, and if there would have been some in-depth teaching of the code part. But this course did benefit.

5.0

Reviewed May 16, 2023

very well-constructed course for deep learning students. Really enjoyed. Many thanks for IBM

4.0

Reviewed May 14, 2020

Good an simple videos to understand the concept. The notebooks are very detailed and give a second layer of knowledge with practical example

5.0

Reviewed May 26, 2020

Not so often i wish a course would be longer and more in depth I really enjoyed using TF I'll look some other courses about it

4.0

Reviewed Nov 21, 2019

Good content. A bit too fast on some complex concepts and missing audio for the last lecture but great lecturer.

All reviews

Showing: 18 of 230

1.0

Reviewed Jan 11, 2020

This course is incomplete, and is NOT recommended.

It uses Tensorflow 1, which is outdated now - should be updated to use Tensorflow 2.

It does not provide practice sessions.

Week 5 - Autoencoder - have no audio, no captions, nothing.

There is no final exam to ensure our competence. No labs we need to be graded on.

This is not a worthy Coursera course. It needs to be withdrawn and updated.

Shinhoo

4.0

Reviewed Nov 17, 2019

The codes need to be updated for TensorFlow 2.0.

Dennis

5.0

Reviewed Nov 6, 2019

course needed to be updated for labs. Now Google moved to Tensorflow 2.0 this year.

lorenzo

1.0

Reviewed Apr 3, 2020

There are 2 main problems with this course:

1 All the codes are for tensorflow version 1 and not 2 which essentially makes them outdated since the new version of tensorflow is quite different from the previous

2 All the explanations are very high level and will leave you with many questions. In short you cna learn as much if not more by watching any youtube videos on each of the topics

In general, the course seems to have been rushed out and the material is ridiculously slim. There is really no reason to take this course. You'll end up frustrated by the simplistic explanations and the fact that you are learning code which won't be relevant in a couple months.

Once again I am so surprised to see a reputable company such as IBM put their name on a product which is frankly embarrassingly bad. There is no way this course would be rated 5 starts by any human being which leads me to believe that they manipulate the scores with fake reviews.

Frank

1.0

Reviewed Dec 18, 2024

The syllabus of this specialization is supposed to be rich; nevertheless, the lectures are not good at all. They mostly read the codes without diving into a proper explanation. The theory background is poor, and the labs don't teach you how to deal with real datasets, just random numbers, nor do they teach you how to implement an entire pipeline of code, just chunks of it without any scope (It seems to me). What could you supposedly expect from modules with lectures of 3 min - 8 min (tops)? I don't recommend this course if you don't have a strong NN background.

Tristan

1.0

Reviewed Jan 9, 2020

This course is a joke. It's a brief overview of a few types of models. Also there is no sound in half the videos.

Martin

4.0

Reviewed Nov 22, 2019

Good content. A bit too fast on some complex concepts and missing audio for the last lecture but great lecturer.

John

4.0

Reviewed Jan 22, 2020

Teaches more on Deep Learning models but less in TensorFlow

Oliver

1.0

Reviewed Jan 2, 2020

Lack of content, quizzes were poor, no sound or transcript on 2 videos. Took about 2 hours total.

Reza

4.0

Reviewed Feb 21, 2025

needed more focus on coding and explanation of codes

Alexey

3.0

Reviewed Feb 5, 2023

Videos are good, but lack of graded coding practice is a big issue with this course. I barely knew how TensorFlow works before starting this course... and this hasn't changed after I finished with 100% grade.

Wei

5.0

Reviewed Feb 19, 2020

I am not sure if no final assessment is a good idea. For the depth of the course it can possibly a major graduation killer but for practical reason you should put that back so people get to be serious with this course.

Zaheer

5.0

Reviewed Jul 3, 2020

Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!

Mr.

5.0

Reviewed Nov 14, 2020

It is very good to explain concept of Deep Learning by Example , it is so clear, and better understand

Shashi

5.0

Reviewed Feb 4, 2020

It helped me to understand how TensorFlow can be used to build the neural networks

4.0

Reviewed Mar 14, 2020

A concise and comprehensive survey of deep learning models. Great labs (which sometimes don't run in IBM Skills Network. Thanks to IBM Watson Studio which came to the rescue in those cases). The labs reinforce concepts and illustrate Tensorflow coding to run the models. Lecturer is very clear and encouraging in tone. Thanks for the course.

Pietro

4.0

Reviewed Jan 5, 2020

Very clear explanation and well organized course. I give 4 stars because videos of Week 5 are missing the audio and subtitles.

Nopthakorn

4.0

Reviewed Dec 31, 2019

Week 5 lecture video no audio

Lab is not update for tensorflow 2