8 Best Deep Learning Certification, Course, Training and Tutorial [2018]

best deep learning courses, certifications, training and tutorials

Whether you want to learn it on the surface or go deep into deep learning, we’ve got you covered. The best courses, training, tutorials and certifications to lead you to a better career. Choose what fits you best and learn it thoroughly.

8 Best Deep Learning Certification, Course, Training and Tutorial [2018]

1. Deep Learning Certification by Andrew Ng from deeplearning.ai

This is undoubtedly one of the most sought after deep learning certifications with Andrew Ng himself teaching the subject. The Co Founder of Global Learning Platform Coursera, Andrew has been the head of Google Brain and Baidu AI group in the past. Joining him are Teaching Assistants, Younes Bensouda Mourri from Mathematical & Computational Sciences at Stanford University and Kian Katanforoosh, Adjunct Lecturer at Stanford University. All in all, we have no doubt in proclaiming this as the Best Deep Learning Certification out there. In this certification course, you will learn about the foundations of Deep Learning, know how to build neural networks and understand all about machine learning projects. There will be real time case studies including sign language reading, music generation and natural language processing among others. Along with all the theory, you will be taught to implement these concepts in Python and TensorFlow.

 

Rating : 4.7 out of 5

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Review : Course content is very good. Andrew Ng’s style of teaching is phenomenal. He has a knack for uncomplicating an otherwise complex subject matter. Highly recommended for anyone who is trying to understand the fundamentals of neural networks and deep learning.

 

 

2. Deep Learning Certification from Microsoft

In this deep learning certification by Microsoft, you will learn an intuitive approach to building complex models that help machines solve real problems. You will need to have basic programming skills, working knowledge of data science before signing up in order to make the most of this program. This course tries to enable engineers / data scientists and technology managers to eventually develop smart understanding of this technology. You will be taught how to use the Microsoft Cognitive Toolkit (CNTK) to tap into data sets through deep learning. Course is taught by Jonathan Sanito, Senior Content Developer at Microsoft, Sayan Pathak Principal ML Scientist and AI School Instructor, CNTK team and Roland Fernandez, Senior Researcher and AI School Instructor, Deep Learning Technology Center, Microsoft Research AI.

 

Rating : 4.4 out of 5

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3. Complete Guide to TensorFlow for Deep Learning with Python

Jose Marcial Portilla has an MS from Santa Clara University and has been teaching Data Science and programming for multiple years now. His training will help you learn how to use Google’s Deep Learning Framework – TensorFlow with Python. He will also teach you how you can use TensorFlow for Image Classification with Convolutional Neural Networks, how to do time series analysis with Recurrent Neural Networks and teach you to solve unsupervised learning problems with AutoEncoders. This training has been attended by close to 20,000 students and has got remarkable reviews and ratings.

 

Rating : 4.6 out of 5

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Review – Excellent course. Portilla sets a pedagogical curve. Responsive Q&A, and reliable and regularly updated course materials are made available. Good foundation to a broad array of well-established and cutting-edge topics, and many useful external resources provided. – Jack Rasmus-Vorrath

 

 

4. Deep Learning A-Z™: Hands-On Artificial Neural Networks

A whooping 72,000 students have attended this training course on Deep Learning. Kirill Eremenko, Hadelin de Ponteves and the SuperDataScience Team, they are pros when it comes to matters of deep learning, data science and machine learning. Even basic high school level mathematics is enough for you to get started with this course and in the 23 hours of on demand video, the trainers will take you through all the necessary knowledge and information required by you to become proficient at deep learning. Specifically, you will learn about the intuition behind Artificial Neural Networks and Convolutional Networks, appying Artificial Neural Networks and Convolutional Networks in practice and much more around Recurrent Neural Networks, Self Organizing Maps and Boltzmann Machines. This is ideally one of the best deep learning course you will find out there.

 

Rating : 4.5 out of 5

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Review – Very nice course! These two instructors know how to explain difficult concepts in simple terms. Kirill is an intuition god, and Hadelin explains every single line of code as you go through the examples. I feel comfortable enough to apply what I learned in this course in my own project. I definitely recommend this course to anyone who wants to understand the basic deep learning concepts and how they are implemented in the real world. – Raoul Noumbissi

 

 

5. Natural Language Processing with Deep Learning in Python

The trainer is a data scientist, big data engineer as well as a full stack software engineer. He has a masters degree in computer engineering with a specialization in machine learning and pattern recognition. With a CV like that, you should already feel assured with the quality of teaching for this deep learning program. This course will be like a complete guide on deriving and implementing GLoVe, word2vec and word embeddings. You will also be taught how to understand and implement recursive neural tensor networks for sentiment analysis. At 6 hours, this is a good crash course for those with not enough time on their hands.

 

Rating : 4.6 out of 5

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Review – Instructor explains things vividly and with detail unlike some other instructors of machine learning. I recommend this course for serious data scientists. – Xiao Qiao

 

 


  Why is Deep Learning Hot Right Now?

6. Modern Deep Learning Course in Python

In this deep learning training spanning 7.5 hours, with full lifetime access, you will learn to apply momentum to back propagation to train neural networks, apply adaptive learning rate procedures like AdaGrad, RMSprop, and Adam, understand the basic building blocks of Theano and then build a neural network in Theano. In addition to understanding TensorFlow, you will also write a neural network using Keras, PyTorch, CNTK and MXNet. In order to attend this program, you will have to be comfortable with Python, Numpy, and Matplotlib. You will have to install Theano and TensorFlow before or during the training.

 

Rating : 4.6 out of 5

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Review – Clear and consistent. Goes over enough of the pre-requisites each course to refresh and remind the student of the foundations and then breaks new ground. Courses are updated often and stay current with the latest versions of the imports API’s. – Bill Hicks

 

 

7. Data Science: Deep Learning Tutorial in Python

This program will serve as a guide for writing a neural network in Python and Numpy using Google’s TensorFlow. The trainer will teach you about how deep learning really works and how a neural network is built from basic building blocks. He will help you demystify various terms related to neural networks like “activation”, “backpropagation” and “feedforward”. There is a live project which is a part of the course to help you implement what you learn in real time.

 

Rating : 4.6 out of 5

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Review – This is a very honest course taught by somebody who clearly understands the subject in great depth. As somebody who has been playing around with Keras, Scikit learn and Tensorflow for over a year, I have learned a huge amount through implementing models taught in this course just using Python. – Malcolm Mason

 

 

8. Deep Learning Tutorial: Recurrent Neural Networks in Python

Know all there is to know about the simple recurrent unit (Elman unit), GRU (gated recurrent unit), LSTM (long short-term memory unit) and also figure out how to write various recurrent networks in Theano in this course around recurrent neural networks in Python. To take up this program, you should know about backpropagation, understand Calculus and Linear Algebra. 10,000+ students have attended this course with great reviews and high ratings.

 

Rating : 4.6 out of 5

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Review – This is the best intro to RNN that I have seen so far, much better than Udacity version in the Deep Learning Nanodegree. I really like the emphasis on the math: although it is not deep but it is clear enough so one get some mathematical intuitions on the working of the Recurrent unit. – Jean-Marc Beaujour

 

So that was our take on the Best Deep Learning courses, tutorials, certifications and training, specially for 2018. Do check out Best Machine Learning Online Course to dive deep into the domain and also Blockchain Training along with Best Python Certification. Since all these courses can be attended online, you have the benefit of carrying on learning from just about anywhere on the planet. We wish you all the best in your career! Team Digital Defynd.

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