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11 Best Paid & Free Deep Learning Courses & Certification of 2020

Deep Learning

Students find it quite hard to meet their needs with many Deep Learning courses. Students also ask us if there is a specific Deep Learning course that fits every event. YES is the answer. You can take part in the popular courses below. Registering for the right course will make a major difference in your career growth. In this article, the best Deep Learning courses & classes in 2020 were chosen by hand.

Our emphasis is on highlighting the best and most famous courses for their respective categories.

Depending on your submission, you can pick the one that best suits your needs.

However, let ‘s look at the best Deep Learning courses on the market.

1. Best Deep Learning Course (deepLearning.ai)

Duration: 4 weeks, 4 to 5 hours per week

Rating : 4.7 out of 5

This is without a doubt one of the most sought after deep learning certifications with Andrew Ng teaching the subject himself. In the past, the co-founder of Coursera Global Learning Site, Andrew has been the head of the Google Brain and Baidu AI division. He is joined by teaching assistants, Younes Bensouda Mourri of Stanford University’s Mathematical & Computational Sciences and Kian Katanforoosh, University Adjunct Lecturer. All in all we have no doubt about proclaiming this out there as the Best Deep Learning Certification.

Key Highlights:

  • Learn about the foundations of Deep Learning in this certification course.
  • Know how to build neural networks and understand everything about machine learning projects.
  • Real-time case studies may include sign language interpretation, music production, and the processing of natural language among others.
  • Learn the theory, Python, and TensorFlow and how to implement these concepts.

You can Sign up Here

2. Complete Guide to TensorFlow for Deep Learning Training with Python (Udemy)

Duration: 14 Hours

Rating : 4.6 out of 5

Jose Marcial Portilla has an MS from the University of Santa Clara and now has been teaching data science and programming for several years. Its certification Tensorflow can help you learn how to use Google’s Deep Learning Platform – Python’s TensorFlow. He will also show you how TensorFlow can be used to classify images with Convolutionary Neural Networks, to analyze time series with Recurrent Neural Networks, and will show you to solve uncontrolled autoencoder learning problems. Nearly 20,000 students participated in the training and have received excellent feedback and ratings.

You can Sign up Here

3. Neural Networks and Deep Learning Certification (Coursera)     

Duration: 4 weeks of study, 3 to 6 hours a week

Rating: 4.9 out of 5

If you look forward to mastering this cutting-edge technology’s principles then this neural network course is worth a try. The curriculum is listed out to address the underpinnings of deep learning and how it works. Analyze the concepts of building, training and applying fully connected deep neural networks and understand the key parameters in architecture of a neural network. That is why basic python programming skills, practical knowledge of data structure and basic ML concepts are required as this is an intermediate level program.

Key Highlights:

  • The necessary installations and set-up of the technical environment are provided with clear guidance.
  • The first few lectures provide a short overview of the scope of the classroom content.
  • Practice and solve problems with usable code to improve your problem-solving skills.
  • Focus on various issues in the real world to see if these AI technologies can be solved.
  • Complete all graded assignments and pass them on to earn the completion badge.
  • This course is a crowd favorite with stellar reviews.

You can Sign up Here 

4. Deep Learning Certification by IBM (edX)

Duration: 7 Months, 2 to 4 hours per week

Rating : 4.6 out of 5

You’ll learn and excel at Deep Learning skills through a series of hands-on assignments and projects throughout this professional certificate program. The course, which is available on renowned e-learning platform edX, will culminate in a Deep Learning capstone project that will help you show prospective employers your applied skills. This program’s trainers are Joseph Santarcangelo, PhD, IBM data scientist; Alex Aklson, PhD, IBM data scientist, and Saeed Aghabozorgi PhD, Sr. IBM Computer Scientist.

Key Highlights:

  • You will learn basic Deep Learning concepts, including various Neural Networks for both supervised and unsupervised learning.
  • You’ll also learn how to create and deploy different forms of Deep Architectures.
  • You will learn to implement Deep Learning architecture Convolutionary Networks, Recurrent Networks, and Autoencoders.

You can Sign up Here

5. Deep Learning Course A-Z™: Hands-On Artificial Neural Networks (Udemy)

Duration: 22.5 Hours

Rating : 4.5 out of 5

A total of 72,000 students participated in this Deep Learning training course. Kirill Eremenko, Hadelin de Ponteves, and the SuperDataScience Team are pros in deep learning, data science, and machine learning matters. Only basic mathematics at the high school level is enough for you to get started with this course and in the 23 hours of on-demand training, the trainers will take you through all the skills and information you need to become fluent in profound thinking. Ideally, this is one of the best deep learning courses that you’ll find out there.

Key Highlights:

  • 23 hours of on-demand training.
  • You’ll learn about the intuition behind Artificial Neural Networks and Convolutional Networks.
  • You will learn the practical application of Artificial Neural Networks and Convolutional Networks, and much more about Recurrent Neural Networks, Self Organizing Maps, and Boltzmann Machines.

You can Sign up Here

6. Deep Learning Nano Degree Program (Udacity)

Duration: 4 months, 12hrs/week

Rating: 4.5 out of 5

Anyone who wants to explore how to construct, implement, and apply their own deep neural networks to different challenges such as classifying the image and generating it, predicting time series, and using the model can use this nano graduate program. This curriculum is designed especially for students interested in doing a career in machine learning, artificial intelligence, or deep learning. Enrolling in this program will introduce you to modules for deep learning, AI and ML algorithms, neural networks, and the deployment of a model for sentiment analysis. Upon completion of the program with given assignments and projects, you will receive a completion certificate that can be shared with your resume and employers.

Key Highlights:

  • Learn how to build and implement neural networks to recognize images, generate sequences and generate images, and how to apply style transfer to your own images.
  • Know the basics of neural networks and build your first Python and NumPy network, as well as learn how to use PyTorch ‘s modern, deep learning framework to build multi-layer neural networks.
  • Including real-world projects, interactive quizzes, graded assignments and hands-on exercises to help improve your learning experience.
  • Get the instructor’s personal career coaching which will assist you at every learning stage.

You can Sign up Here

7. Natural Language Processing with Deep Learning in Python

Duration: 12 Hours

Rating : 4.6 out of 5

The lecturer is a computer scientist, Big Data Developer and software designer with full stack. He holds a computer engineering masters degree with a specialization in machine learning and pattern recognition. With such a CV, you should already feel assured of the teaching quality for this deep learning programme. This course will be like a complete tutorial on GLoVe, word2vec and word embedding deriving and implementation. You will also be taught how to analyze sentiment by understanding and implementing recursive neural tensor networks. For those with not enough time on their hands, this is a good crash course at 6 hours.

You can Sign up Here

8. Free Deep Learning Course from Microsoft (edX)

Duration: 6 Weeks, 4 – 8 hours/week

Rating : 4.4 out of 5

With this Microsoft deep learning certification, you’ll learn an intuitive approach to building complex models that help machines solve real issues. Before signing up you will need basic programming skills, working knowledge of data science to make the most of this programme. This course attempts to enable engineers/data scientists and technology managers to develop a smart understanding of this technology in the end. You will be taught how to use the Microsoft Cognitive Toolkit (CNTK) to tap deep learning into the data sets. 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, will teach the course.

You can Sign up Here

9. Modern Deep Learning Course in Python

Duration: 9.5 Hours

Rating : 4.6 out of 5

In this 7.5-hour deep learning session, with full-life access, you’ll learn how to apply momentum to back propagation to train neural networks, apply adaptive learning rate procedures such as AdaGrad, RMSprop, and Adam, understand Theano’s basic building blocks and then create a neural network in Theano. Besides understanding TensorFlow, you’ll also use Keras, PyTorch, CNTK and MXNet to write a neural network. You’ll need to be familiar with Python, Numpy, and Matplotlib to join this course. Before or during the training you’ll need to install Theano and TensorFlow.

You can Sign up Here

10. Deep Learning Course: Recurrent Neural Networks in Python

Duration: 11 Hours

Rating : 4.6 out of 5

Know more about the simple recurring unit (Elman unit), the GRU (gated recurrent unit), the LSTM (long short-term memory unit) and how to compose various recurrent Theano networks around recurrent neural networks in Python. You should know about backpropagation, understand Calculus and Linear Algebra to take this program on board. This course was attended by 10,000 + students, with positive reviews and high scores.

You can Sign up Here

11. Data Science: Deep Learning Course in Python

Duration: 11 Hours

Rating : 4.6 out of 5

Using Google’s TensorFlow this program will serve as a guide to writing a neural network in Python and Numpy. The trainer will teach you how deep learning actually works, and how the basic building blocks build a neural network. He will help you to demystify various neural network terms such as “activation,” “backpropagation” and “feedforward.” There is a live project that is a part of the course to help you realize what you are learning in real time.

You can Sign up Here

Wrapping Up

That’s the list of Deep Learning courses with high-quality content. They are popular and loved by many machine learning students. Between these courses, you are sure to find what you need to learn to continue your path of Deep Learning.

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