Every day it seems there is a new headline for how deep learning is changing the world around us. A few examples:

• Deep learning algorithm diagnoses skin cancer as well as seasoned dermatologists
• Amazon Go: How Deep Learning and AI will change Retailing
• Deep Learning Makes Driverless Cars Better at Spotting Pedestrians

Want to see what the fuss is all about? Looking to master the technical content to advance your career or start your own company? Here are 23 online courses that cover everything from the basics of deep learning to the most cutting edge research today.

Before we start, you may be asking yourself, “What is deep learning?” Here is a succinct description from Jason Brownlee from Machine Learning Mastery: “deep learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.”

Without further ado…

Online Deep Learning Courses

Creative Applications of Deep Learning with TensorFlow
via Kadenze
★★★★★ (13 ratings)

We cover the basic components of deep learning, what it means, how it works, and develop code necessary to build various algorithms such as deep convolutional networks, variational autoencoders, generative adversarial networks, and recurrent neural networks. A major focus of this course will be to not only understand how to build the necessary components of these algorithms, but also how to apply them for exploring creative applications.

Prominent review (by Christopher Kelly): “I have an undergraduate degree in computer science … I’ve spent a ton of time on Khan Academy and Coursera and I’m blown away by the quality and professionalism of the content of this course. Highly recommended!”

Deep Learning Specialization
deeplearning.ai via Coursera

This specialization on Coursera is taught by Stanford professor Andrew Ng, the co-founder of Coursera. The Deep Learning Specialization consists of five different courses. The courses are free to take, but you need to sign up for a subscription of $49/month if you want access to the graded assignments or earn certificates. There is a seven day free trial. The individual courses are free, but you need to visit the course pages separately; you cannot sign up to them from the Specialization page. The five courses are as follows:

1. Neural Networks and Deep Learning  (You can read Class Central’s in-depth review for the Andrew Ng’s first course here.)
2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization
3. Structuring Machine Learning Projects
4. Convolutional Neural Networks
5. Sequence Models

Neural Networks for Machine Learning
University of Toronto via Coursera
★★★★★ (14 ratings)

Learn about artificial neural networks and how they’re being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We’ll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

Prominent review (by Bobby Brady): “This is one of those chance in a lifetime courses you have to get to learn from the greats. Geoffrey Hinton was one of the most important and influential researchers to work on artificial intelligence and neural nets back in the 80’s. Currently he is working with Google in their AI/deep learning initiatives.”

Professor Geoffrey Hinton, who teaches Neural Networks for Machine Learning

Practical Deep Learning For Coders, Part 1
fast.ai
★★★★★ (1 rating)

This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems.

Prominent review (by Anonymous): “This is really a hidden gem in a field that rapidly growing. Jeremy Howard does an excellent job of both walking through the basics and presenting state of the art results. I was surprised time and again when not only was he presenting material developed within the last year, but even within the week the course was running … You practice on real life data through Kaggle competitions. I would strongly recommend this course to anyone looking to go from zero real world experience to competing with experts in the field.”

Deep Learning
Google via Udacity
★★☆☆☆ (13 ratings)

In this course, you’ll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets. You will learn to solve new classes of problems that were once thought prohibitively challenging, and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.

Deep Learning for Natural Language Processing
University of Oxford 

This will be an applied course focusing on recent advances in analysing and generating speech and text using recurrent neural networks. We will introduce the mathematical definitions of the relevant machine learning models and derive their associated optimisation algorithms.

6.S191: Introduction to Deep Learning
Massachusetts Institute of Technology

A week-long intro to deep learning methods with applications to machine translation, image recognition, game playing, image generation and more. A collaborative course incorporating labs in TensorFlow and peer brainstorming along with lectures.

Deep Learning Summer School 2015 and 2016
Various organizers (including Yoshua Bengio and Yann LeCun) via Independent

Deep Learning Summer School is aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research.

Online Course on Neural Networks
Hugo Larochelle/Université de Sherbrooke

“Welcome to my online course on neural networks! I’ve put this course together while teaching an in-class version of it at the Université de Sherbrooke. This is a graduate-level course, which covers basic neural networks as well as more advanced topics.”

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The following courses are all hosted on Udemy. The courses provided by Lazy Programmer Inc. are in their suggested order as per the “Useful Course Ordering” guideline in their course descriptions.

Deep Learning A-Z™: Hands-On Artificial Neural Networks
Kirill Eremenko and the SuperDataScience Team via Udemy
4.7 stars (388 ratings)

Learn to create deep learning algorithms in Python from two machine learning and data science experts. Templates included. This course is taught by the same instructor that teaches my top recommendation for intro to data science courses.

Zero to Deep Learning™: Mastering Keras
Data Weekends, Jose Portilla, Francesco Mosconi
4.8 stars (23 ratings)
Understand and build Deep Learning models for images, text, sound and more using Python and Keras.

Deep Learning Prerequisites: The Numpy Stack in Python
Lazy Programmer Inc. via Udemy
4.6 stars (917 ratings)

The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence.

Deep Learning Prerequisites: Linear Regression in Python
Lazy Programmer Inc. via Udemy
4.6 stars (579 ratings)

Learn linear regression from scratch and build your own working program in Python for data analysis.

Deep Learning Prerequisites: Logistic Regression in Python
Lazy Programmer Inc. via Udemy
4.6 stars (448 ratings)

Data science techniques for professionals and students – learn the theory behind logistic regression and code in Python.

Data Science: Deep Learning in Python
Lazy Programmer Inc. via Udemy
4.6 stars (906 ratings)

A guide for writing your own neural network in Python and Numpy, and how to do it in Google’s TensorFlow.

Data Science: Practical Deep Learning in Theano + TensorFlow
Lazy Programmer Inc. via Udemy
4.6 stars (179 ratings)

Take deep learning to the next level with SGD, Nesterov momentum, RMSprop, Theano, TensorFlow, and using the GPU on AWS.

Deep Learning: Convolutional Neural Networks in Python
Lazy Programmer Inc. via Udemy
4.6 stars (191 ratings)

This course is all about how to use deep learning for computer vision using convolutional neural networks. These are the state of the art when it comes to image classification and they beat vanilla deep networks at tasks like MNIST.

Unsupervised Deep Learning in Python
Lazy Programmer Inc. via Udemy
4.6 stars (97 ratings)

Autoencoders and Restricted Boltzmann Machines for Deep Neural Networks in Theano, and t-SNE and PCA.

Deep Learning: Recurrent Neural Networks in Python
Lazy Programmer Inc. via Udemy
4.6 stars (153 ratings)

GRU, LSTM, and more modern deep learning, machine learning, and data science for sequences.

Natural Language Processing with Deep Learning in Python
Lazy Programmer Inc. via Udemy
4.6 stars (123 ratings)

Complete guide on deriving and implementing word2vec, GLoVe, word embeddings, and sentiment analysis with recursive nets.

Unleash Deep Learning: Begin Visually with Caffe and DIGITS
Razvan Pistolea via Udemy
4.3 stars (34 ratings)

An introduction to Deep Learning tools using Caffe and DIGITS where you get to create your own Deep Learning Model.

Deep Learning with TensorFlow
Packt Publishing via Udemy
4.1 stars (62 ratings)

Channel the power of deep learning with Google’s TensorFlow!

Deep Learning with Python
Packt Publishing via Udemy
3.7 stars (27 ratings)

Dive into the future of data science and implement intelligent systems using deep learning with Python.

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Though it is more of a program than a singular online course, below you’ll find a Udacity Nanodegree targeting the fundamentals of deep learning. At time of publishing, the current enrollment period is closed, but you can sign up for the waiting list to be notified when the next enrollment period begins.

Deep Learning Foundations Nanodegree
Siraj Raval via Udacity

Artificial Intelligence is transforming our world in dramatic and beneficial ways, and Deep Learning is powering the progress. Together with Siraj Raval, Udacity provides a dynamic introduction to this amazing field, using weekly videos, exclusive projects, and expert feedback and review to teach you the foundations of this future-shaping technology.

https://vimeo.com/199252593