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10 Best Deep Learning Training & Courses Online [Updated 2020]

 

Deep Learning is among the most in demand skills in technology today. Deep Learning engineers are highly sought after, and a profound understanding of Deep Learning will provide you many new livelihood opportunities. It is also a brand new superpower which will allow you to build AI systems which were not possible a couple of years ago. Self-driving automobiles are travelling countless kilometers, IBM Watson is currently diagnosing patients better than physicians and Google Deepmind’s AlphaGo conquered the World winner at Go – a match in which intuition played an integral role. Nevertheless, with the additional AI improvements, the issues it ought to fix have also become more complex. And only Deep Learning may resolve these complex issues and that is the reason why it lies at the center of Artificial intelligence. Undoubtedly, the demand for deep learning online courses is also increasing.

 

Deep learning is an integral enabler of all AI powered technology being developed throughout the world. And lastly, the share of occupations requiring AI abilities has increased 4.5x since 2013. If all these reasons are good enough for you to foray into the field of Deep Learning then you ought to have the best deep learning course online by your side. And for the same reason, we here at TrumLearning, along with a team of 10 deep learning and machine learning experts have developed a list of the best deep learning course online for you. These courses on the course list will not only provide information on what is required out there but also teach you on how to skillfully use the knowledge you’ve obtained after much hard work. So without further ado, let’s dive right in.

 

Best Deep Learning Online Courses, Training & Certification

  1. Deep Learning Specialization by DeepLearning.ai [Coursera]
  2. Neural Networks and Deep Learning by DeepLearning.ai [Cousera]
  3. Hands-on artificial intelligence by IBM [EdX]
  4. Complete Guide to TensorFlow for Deep Learning with Python [Udemy]
  5. Deep Learning A-Z™: Hands-On Artificial Neural Networks [Udemy]
  6. Natural Language Processing with Deep Learning in Python [Udemy]
  7. Modern Deep Learning in Python [Udemy]
  8. Deep Learning Explained by Microsoft [EdX]
  9. Data Science: Deep Learning in Python [Udemy]
  10. Deep Learning Nanodegree [Udacity]

 

1. Deep Learning Specialization [Coursera]

 

For those looking to master deep learning rather than just scratching the surface, this deep learning online course seems to be the perfect resource. Because first of all, let us correct ourselves. This is not a standalone best deep learning certification ‘course’ but rather a specialization. Offered by deeplearning.ai themselves, this deep learning training specialization will help you break into AI. From learning the foundations of Deep Learning via this coursera deep learning specialization, building neural networks, to leading machine learning projects that can be considered to be successful, this 5-course coursera deep learning specialization covers everything that you need to know in-depth. Mainly Convolutional networks, RNNs, LSTM, Adam, along with Dropout, BatchNorm, and Xavier/He initialization, are just some of the advanced areas that this deep learning course explores but there is lot more than that as well.

 

The specialization has the following 5 deep learning training courses:

 

The major topics covered in this one of the best deep learning certification specialization course are:

  • Neural Networks Basics
  • Deep Neural Networks
  • Hyperparameter tuning, Batch Normalization and Programming Frameworks
  • Practical aspects of Deep Learning
  • Machine Learning Strategy
  • Deep convolutional models
  • Face recognition & Neural style transfer
  • Natural Language Processing & Word Embeddings
  • Sequence models & Attention mechanism
  • Recurrent Neural Networks

 

It should not take you more than 3-months to complete if you go at the suggested pace of 11-hours per week

 

Reviews by student:

I want to learn new things, because that’s what brings joy to my life. With Coursera, I can meet and interact with others who feel the same way.

Harry S.

 

2. Neural Networks and Deep Learning [Cousera]

 

And if you are just interested in learning about Neural Networks, then you can simply go for one this deep learning certification course from the above mentioned Deep Learning Specialization. Not only you will learn the foundations of deep learning in this part course of coursera deep learning specialization, but also you will explore popular and advanced concepts like the major technology trends driving Deep Learning, building, training and applying fully connected deep neural networks, and finally implementing efficient (vectorized) neural networks. Instead of just a surface-level description, this best deep learning course online also teaches you about how Deep Learning actually works. Taking up a part of the deep learning specialization will not only allow you to apply deep learning to your own applications, but also answer basic interview questions in case you are looking for a job in this field.

 

The core concepts that have been discussed in this deep learning training are:

  • Introduction to deep learning
  • Neural Networks Basics
  • Shallow neural networks
  • Deep Neural Networks
  • Derivatives with a Computation Graph
  • Vectorizing Logistic Regression

 

This course is the first one in the recommended chronology of the Deep Learning Specialization and should take you approximately 18-hours to complete.

 

Reviews by student:

I want to learn new things, because that’s what brings joy to my life. With Coursera, I can meet and interact with others who feel the same way.

Harry S.

 

3. Hands-on artificial intelligence [EdX]

 

Offered by IBM, this deep learning professional certificate program is a group of 5 deep learning training courses. It starts with the fundamental concepts of Deep Learning including Neural Networks and teaches you how to apply the popular libraries like Keras, PyTorch, and Tensorflow to the industry problems. From building, training, and deploying various Deep Architectures to apply your knowledge to real-world scenarios, namely object recognition and Computer Vision, this deep learning training program is a perfect blend of theory and practical. Finally, it will help you gain mastery over Deep Learning by making use of accelerated hardware and GPUs.

 

 

Here is a list of the 5 deep learning training courses that make up this program:

 

Major topics covered via this deep learning certification program are:

  • Artificial Neural Networks
  • Deep Learning Libraries
  • Linear Regression
  • Computer Vision Networks
  • Convolutional Neural Networks (CNN)
  • Restricted Boltzmann Machine
  • Distributed Deep Learning
  • Deep Learning in the Cloud
  • How to build a Deep Learning model
  • Deep Learning pipeline

 

A series of hands-on labs, assignments, and projects throughout the deep learning training course will help you enhance your learning and better commit it to your memory. At the recommended pace of 2-4 hours per week, you should not take more than 7 months to complete this course. The end of the deep learning specialization program also provides you with a ‘Job Outlook’ section that tells you about the various fields that you can get into and the annual average salary if you choose to master Deep Learning.

 

Reviews by student:

This is a good TF overview course, full of hand on examples and adequate background theory. Deep Learning NN is a deep subject. The course does a good job explaining the key NN concepts without getting lost in the details. I have a TF book to supplement this course which really helps in alternating between the hand on and the theory. I am looking forward to the TF 2.0 course. This course will go a long way toward preparing for TF 2.0 as you already have ahd the foundations.

Mark Mneimneh

 

4. Complete Guide to TensorFlow for Deep Learning with Python [Udemy]

 

This deep learning online course revolves around teaching its students about Google’s Deep Learning Framework – TensorFlow with Python. This 14-hour video course teaches you about  the complexities of Google’s TensorFlow framework in an easy to understand way. The USP of this deep learning training course is that it deliberately involves Tensorflow unlike other deep learning certification courses out there which stay away from pure tensorflow. Instead they use abstractions to make things easier but that results in less user control. You will also be delving into the latest available techniques as per the industry standards in this deep learning online course.

 

The major topic which this deep learning training focuses on are:

  • How Neural Networks Work
  • TensorFlow for Classification
  • Reinforcement Learning with OpenAI Gym
  • Building your own Neural Network
  • TensorFlow for Image Classification
  • Generative Adversarial Networks

 

This course makes sure that there is harmony between theory and practical implementations in the teachings. Further, there are plenty of exercises to help you learn by doing.This course is certainly not for complete beginners as it requires you to have some knowledge of Python programming and basic math knowledge like mean, and standard deviation.

 

Reviews by student:

I had no doubt about the quality of this course as I had already done their Machine Learning course. For those looking for a beginner to intermediate level of knowledge in Deep Learning, I would definitely recommend this course, as the concepts are explained very clearly and in simple language. This also helps in advance level knowledge as the basic concepts become clear.

Anshul Vankar

 

5. Deep Learning A-Z™: Hands-On Artificial Neural Networks [Udemy]

 

This 22.5-hour deep learning certification course will teach you how you can create Deep Learning Algorithms in Python. Two Machine Learning & Data Science experts will hold your hand and take you on a step-by-step journey about how  It will be making use of a robust deep learning training course structure to divide the learning into easily understandable segments i.e. Supervised Deep Learning and Unsupervised Deep Learning. Here in this course, each volume would be focusing on three distinct algorithms. It places special emphasis on making you understand why you are doing what you are doing in an intuitive way rather than just bombarding you with theory, and math, and coding. Such an approach would prove to be significantly helpful in the hands-on coding exercises and you will have a much more meaningful experience.

 

The core concepts taught in this deep learning certification course are:

  • Intuition behind Artificial Neural Networks
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Self-Organizing Maps
  • Boltzmann Machines
  • Applying AutoEncoders

 

The speciality of this deep learning certification course is that you will be working on Real-World datasets, to solve Real-World business problems. Customer Churn problem, Image Recognition, Stock Prices, Fraud Detection, and Recommender Systems are some of the problem areas that you would be working on. And lastly, this deep learning course explains in great details about the Stacked Autoencoder which will enable you to challenge Netflix for a $1 Million prize.

 

Reviews by student:

This is a serious look at some NLP methods from the deep learning era. Can’t say anyone else explains it so well. Everything is broken down piece by piece.

Imran Muhammad

 

6. Natural Language Processing with Deep Learning in Python [Udemy]

 

This comprehensive 13-hour deep learning course is a complete hands on guide for deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets. This is an advanced level deep learning certification course which requires a lot of existing knowledge namely, understanding backpropagation, coding a recurrent neural network, and coding a feedforward neural network. The course mainly deals with advanced NLP unlike other deep learning online courses. You will be learning 4 new architectures in this course, right from theory to implementation. The course will also teach you how to solve some classical NLP problems, like parts-of-speech tagging and named entity recognition through recurrent neural networks.

 

The main concepts discussed in this deep learning certification course are:

  • Skip-gram method
  • Gradient descent and alternating least squares
  • Named entity recognition
  • Recursive neural tensor networks
  • Negative sampling optimization
  • Pre Trained word vectors from GloVe

 

Any material required for this best deep learning course can be downloaded and installed for free as they are all open source. Primarily, you will be dealing with Numpy, Matplotlib, and Theano to get most of the work done. You will work with a “how to build and understand” approach, and not just with a “how to use” mindset.

 

7. Modern Deep Learning in Python [Udemy]

 

The crux of this deep learning course lies on teaching you how to use modern libraries like Tensorflow, Theano, Keras, PyTorch, CNTK, MXNet. This 9.5-hour deep learning certification course is a successor of the  Deep Learning in Python course and thus expects you to be well versed in Numpy, Python, probability and statistics. It is particularly for those individuals who are looking to improve their skills with neural networks and deep learning. Unlike other deep learning online courses, via the batch and stochastic gradient, you will learn how to train on just a small sample of the data at each iteration, and thus greatly speed up the training time involved. You will further learn about momentum, to carry you through local minima and therefore avoid a slow learning rate.

 

The primary topics covered in this deep learning course are:

  • Applying momentum to backpropagation
  • Basic building blocks of Theano
  • Writing a neural network using CNTK
  • Full, batch, and stochastic gradient descent
  • Batch normalization in Theano and Tensorflow
  • Weight Initialization

 

This deep learning training requires you to be absolutely comfortable with Python, Numpy, and Matplotlib to make sure that you understand the course content well. The course believes in the ideology of testing your skills via experimentation and see for yourself rather than just remembering facts useless facts. Lastly, you will also learn about adaptive learning rate techniques like AdaGrad, RMSprop, and Adam. These too will bring in the results of decreasing training time.

 

Reviews by student:

This material of this course is must-know before progressing to more advanced neural network architectures. Particularly great in my opinion were the sections on momentum and adaptive learning rates as well as weight initialization. The topics covered aren’t trivial but the instructor does a great job at breaking down the math.

Timo K.

 

8. Deep Learning Explained [EdX]

 

This Microsoft offered EdX deep learning training course lays emphasis on helping you develop an intuitive approach to building the complex models. This deep learning certification course is part of a Professional Certificate program offered by EdX. The intuitive approach that you develop will then be translated into a working code. This will help you deal with real world practical problems and gain significant hands-on experience. Not only will you derive insights from these models using Python Jupyter notebooks, but also leverage the Microsoft Azure Notebooks platform for free. Engineers / data scientists / technology managers and other related professionals would be ecstatic to go through the contents of this one of the best deep learning course as it presents the required knowledge in a very detailed format.

 

The main topics covered in this course are:

  • Simple multi-class classification model
  • Components of a deep neural network
  • MLP, CNN, RNN, LSTM
  • Algorithms used in deep learning
  • End-to-end model for recognizing hand-written digit images
  • Building a text data application

 

At the end, unlike deep learning online courses, you will also learn how to use the Microsoft Cognitive Toolkit, to help you harness the intelligence within massive datasets in a speedy, and accurate way through uncompromised scaling. This is an intermediate level deep learning course that should not take you more than 6 weeks to complete if you maintain the suggested pace of 4–8 hours per week. All EdX courses are free to take and you would only be required to pay for the certification.

 

9. Data Science: Deep Learning in Python [Udemy]

 

This is undoubtedly one of the most in-depth deep learning training courses available on Udemy for understanding neural network theory. Building on the learning from the Deep Learning Prerequisites: Logistic Regression in Python course, this deep learning course will help you build a non-linear neural network using Python and Numpy. A binary classification model will be extended to multiple classes using the softmax function. Further, unlike other deep learning online courses, you’d be learning about the all important backpropagation function and learn to code it in Numpy, first the slower way, and then the faster way. The Google’s new TensorFlow library will also be utilized to build another neural network. This deep learning certification course talks beyond the basic models of logistic regression and linear regression and instead tries to build something that learns automatically.

 

The major topics covered in this deep learning training course are:

  • Neuron Training
  • E-Commerce Course Project
  • Feedforward in Slow-Mo
  • Categorical Cross-Entropy Loss Function
  • Neural Networks for Regression
  • Facial Expression Recognition in Code

 

This 10.5-hour course requires you to be well versed in basic math including calculus derivatives, matrix arithmetic, probability and concepts of logistic regression like cross-entropy cost, gradient descent, neurons, XOR, donut. It is full of practical examples and projects like predicting user actions on a website, the number of products they viewed, session duration, etc. which provide a great opportunity to learn by doing.

 

Reviews by student:

In depth explanation of maths behind ANN helps lay a solid foundation for data scientists as LP suggests. Besides, the coding style is also industrial applicable. This is the course I should know earlier. 5 stars for sure.

Amplio

 

10. Deep Learning [Udacity]

 

This is not a standalone deep learning training course but rather a nanodegree program by Udacity. Offered in collaboration with Amazon Web Services (AWS) and Facebook Artificial Intelligence, it requires you to have an intermediate level experience with Python, and some familiarity with calculus and linear algebra to better understand the deep learning training course content. And if you have some basic knowledge of machine learning, then it would prove to be even more beneficial, however, it is not compulsory to have it. The course will take you from being a complete newbie to making you an expert in neural networks, by teaching you to implement them via a deep learning framework called the PyTorch.

 

Primary areas covered in this deep learning course are:

  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Generative Adversarial Networks
  • Deploying a Sentiment Analysis Model
  • Predicting Bike-Sharing Patterns
  • Generating TV scripts

 

The deep learning training course should not take you more than 4-months to complete it at the suggested pace of 12 hours per week. It will make you work on real world projects and gain feedback from experts so as to maximize the results of this course. Beside all the learning in the course, you also get access to personal career coach and career services.

 

Reviews by student:

This is probably the most approachable way to get into deep learning I have found thus far. The course covers a lot of interesting subjects, with (usually) good explanatory videos and walkthroughs. These always feel fresh and get you motivated for the subjects you are about to learn. As a bonus, they have gotten a few known names to present individual subjects. As an example, the introduction to GANs is done by none other than the inventor himself, which is a cool bonus. There is a lot of great material here, and while some of it feels a bit rushed or oversimplified at times, they do reference more material for those that want to dive deeper into the learning B). (That being said, you will definitely have to get your hands dirty at times as well.) The main value here is in the projects and introductory notebooks. Here, you’ll get a lot of hands on experience writing code, and you will definitely feel like you’ve come a long way after finishing them all. Best of all, you’ll have working code that you can tweak and use for your own projects afterwards, and perhaps a ton of ideas as well. All in all, money well spent, at least in my case.

Peter L.

 

Conclusion

The field of Deep Learning has only been growing in the past and the trend will continue owing to advancements in technology and with it the need for machines to handle complex situations. This deep learning training course list will help you learn from the experts of the industry and showcase your skills in a way that will make you stand out from the crowd. Whether your objective is to incorporate Deep Learning into your business or achieve industry specific skills for your next dream job, it requires humongous efforts on your part. We have introduced you to the right deep learning training resources and now the learning part lies on you. See you in the next article!

 

Best Deep learning Course Certification Training Online Reviewd by 10 Deep Learning Experts 4.7