There’s a plethora of Deep Learning MOOCs online, and Edgy Labs helps you find the best online courses to teach yourself and advance your career, free of charge.

To compile this list, we explored Deep Learning MOOCs (Massive Open Online Courses) published by top universities, colleges, and leading tech companies.

Dedicated to beginners, intermediate, and advanced learners, and covering most concepts of Deep Learning, from the most basic to the cutting-edge, all of these courses are free and self-paced, and some of them even offer certificates.

It goes without saying that all of these courses come with some prerequisites: basic knowledge of mathematics, how to manipulate GitHub repositories, and a good command of programming languages like Python.

Here are our top 10 free Deep Learning MOOCs, in no particular order:

1. Deep Learning by Google

Google has published an online course dedicated to deep learning via Udacity, the online course platform.

Google’s MOOC trains intermediate to advanced developers free of charge for 12 weeks on many aspects of deep learning, such as how to build and optimize deep neural networks.

The course is developed by Vincent Vanhoucke, a lead technical scientist at Google’s Brain team.

2. Neural Networks and Deep Learning

Via Class Central and Coursera, this MOOC, from Stanford University and deeplearning.ai, is taught by Stanford Professor and Coursera founder Andrew Ng.

Read More: Andrew Ng: Everyone Should Master Machine Learning

This course teaches you the basics of deep learning, and by the end of the class, you’ll know how to build, train and manage deep neural networks, and apply them to your own projects.

3. Algorithms: Design and Analysis

Because algorithms are at the heart of Deep Learning and computer science in general, this course from Stanford University will introduce you to algorithms.

Dedicated to learners who have at least a little programming experience, in Part 1 of this course you’ll learn about “Big-oh” notation, data sorting and searching, divide and conquer method, randomized algorithms, data structures, and graph primitives.

After you finish this class, you can register for Part 2 and dive deeper into algorithms.

4. Machine Learning

This is a 14-week-long MOOC, at 8-10 hours a week, from the Georgia Institute of Technology.

In this course, you’ll learn supervised and unsupervised machine learning, randomized search algorithms, Bayesian learning methods, reinforcement learning and several other Machine Learning concepts.

5. Improving Deep Neural Networks

This is another MOOC from Stanford University and deeplearning.ai.

This 3-week-long course addresses hyperparameter tuning, regularization and performance optimization of deep neural networks.

Though the course is free, it does offer paid certificate.

6. Deep Learning Lecture

Nando de Freitas is a machine learning professor at the University of British Columbia.

Freitas has put together a series of YouTube videos, where he gives courses on Deep Learning. The channel has 16 videos that vary in length.

He also has 33 videos on Machine Learning for undergraduates.

7. Neural Networks for Machine Learning

This MOOC, published by the University of Toronto, is intended for intermediate learners who have a basic understanding of Python.

Over the 16 weeks that this class takes, you can learn about deep neural networks and their varied applications, such as speech recognition, object recognition, image segmentation, etc.

The course is available as a free or paid offering and includes a paid certificate.

8. Creative Applications of Deep Learning with TensorFlow

Published by the Kadenze Academy, this free course teaches you the basic components that you’ll need to build a variety of algorithms: deep convolutional neural networks, variational autoencoders, generative adversarial networks, and recurrent neural networks.

After you understand how to build Deep Learning networks, you can go further into the course and learn about their creative applications.

9. Introduction to Deep Learning

This free course is published by the Massachusetts Institute of Technology (MIT).

This is a week-long, self-paced course that will introduce you to Deep Learning technology and many of its industrial applications, from translation algorithms to image and object recognition, game playing, and more.

10. Deep Learning for Self-Driving Cars

Here’s another free Deep Learning class from MIT, but that’s dedicated to autonomous cars.

Designed for beginners, but it can be beneficial to advanced learners as well, this course is an intro to Deep Learning systems for self-driving car and semi-autonomous vehicles.

The class comes with five video lectures, each dealing with a specific Deep Learning method within the theme of self-driving cars.

Have you taken any of these courses? What was your experience? 

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