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Our team of global experts has compiled this list of the 10 Best +Free Deep Learning Certification, Course, Training and Tutorial available online in 2019 to help you Learn Deep Learning. These are suitable for beginners, intermediate learners as well as experts.
10 Best Deep Learning Courses [UPDATED]
1. Best Deep Learning Course (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. Neural Networks and Deep Learning Certification (Coursera)
If you are looking forward to grasping the concepts of this cutting-edge technology then this neural network course is worth a try. The curriculum is chalked out to cover the foundations of deep learning and how it actually works. Explore the concepts to build, train and apply fully connected deep neural networks and understand the key parameters in a neural network architecture. As this is an intermediate level program, therefore, basic python programming skills, practical knowledge of data structure and basic ML concepts are required.
Key USPs-
Clear guidance is provided to go through with the necessary installations and setup of the technical environment.
The first few lectures provide a brief introduction to the scope of the content covered in the classes.
Practice with available code and solve assignments to enhance your problem-solving competence.
Work on different real-world problems, and see how they can be solved with these AI technologies.
Complete and pass all the graded assignments to earn the completion badge.
With stellar reviews, this course is a crowd favorite.
Duration: 4 weeks of study, 3 to 6 hours a week
Rating: 4.9 out of 5
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Review : I had started my journey into deep learning as a noob and now i feel confident of the concepts that I've been developing over time. This is the first time I could be confident while answering the questions. All thanks to the best professor Andrew Ng.
3. Deep Learning Certification by IBM (edX)
Throughout this professional certificate program, you will learn and excel at Deep Learning skills through a series of hands-on assignments and projects. Available on renowned elearning platform edX, the course will culminate into a Deep Learning capstone project that will help you showcase your applied skills to prospective employers. Among other things, you will learn fundamental concepts of Deep Learning, including various Neural Networks for both supervised and unsupervised learning. You will also learn how to build and deploy different types of Deep Architectures including Convolutional Networks, Recurrent Networks as well as Autoencoders. The trainers of this program are Joseph Santarcangelo, PhD., Data Scientist IBM; Alex Aklson, Ph.D., Data Scientist at IBM and Saeed Aghabozorgi PhD, Sr. Data Scientist IBM. In case you are interested, we have a compilation of R Certification as well.
Rating : 4.6 out of 5
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4. Complete Guide to TensorFlow for Deep Learning Training with Python (Udemy)
Jose Marcial Portilla has an MS from Santa Clara University and has been teaching Data Science and programming for multiple years now. His Tensorflow Certification 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. If you are interested, you can check out our compilation of Data Scientist Certification as well.
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
5. Deep Learning Course A-Z™: Hands-On Artificial Neural Networks (Udemy)
A whopping 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 Best Deep Learning Certification [2019] [UPDATED]
6. 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. You can also have a look at some of the best natural language processing courses.
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
7. 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
8. Free Deep Learning Course from Microsoft (edX)
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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9. Data Science: Deep Learning Course 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
10. Deep Learning Course: 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
We wish you all the best in your career! Team Digital Defynd.
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