7 Best Deep Learning Courses on Coursera in 2021

Aqsazafar
9 min readMar 20, 2021

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Coursera has a wide range of Machine Learning and Deep Learning courses. That’s why I thought to list some Best Deep Learning Courses on Coursera. So give your few minutes and find out Best Deep Learning Courses on Coursera for you

Best Deep Learning Courses on Coursera

But before I discuss the deep learning courses, I would like to tell you Why Deep Learning is more powerful than machine learning?

Why Deep Learning?

The main three reasons for using Deep Learning are-

  • Deep Learning gives excellent results on large datasets. But Machine Learning algorithms fail to process huge datasets. Machine Learning can work only on small datasets. This is the limitation of Machine Learning. But Deep Learning can easily perform operations on large datasets.
  • In Machine Learning, you need to feed all features manually to train the model. But Deep Learning automatically extracts all the features. This makes Deep Learning much powerful than Machine Learning. Because manual feeding is a time-consuming process, especially if you have a large dataset.
  • Machine Learning can’t solve complex real-world problems. But Deep Learning Algorithms can easily solve real-world problems. That’s why many fields are using Deep Learning algorithms over Machine Learning.

I hope now you understood the importance of deep learning. Now without further ado, let’s start finding the Best Deep Learning Courses on Coursera-

1. Deep Learning Specialization

Provider- deeplearning.ai

Instructor- Andrew Ng, Younes Bensouda Mourri, Kian Katanforoosh

Rating- 4.8/5

Time to Complete- 4 months ( If you spend 5 hours per week)

This is one of the best deep learning specialization programs created by Andrew Ng the Co-founder of Coursera and an Adjunct Professor of Computer Science at Stanford University.

This is a Specialization Program that contains 5 courses. Python and TensorFlow are used in this specialization program for Neural networks. This is the best follow-up to Andrew Ng’s Machine Learning Course.

This Deep Learning Specialization is an advanced course series for those who want to learn Deep Learning and Neural networks. More than 250,000 learners from all over the globe have already enrolled in this Specialization Program.

Now, let’s see all the 5 courses of this Specialization Program-

Courses Include-

  1. Neural Networks and Deep Learning
  2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization
  3. Structuring Machine Learning Projects
  4. Convolutional Neural Networks
  5. Sequence Models

Extra Benefits-

  • You will get a Shareable Certificate.
  • You will get a chance to work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing.
  • Along with that, you will get a chance to hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.

Who Should Enroll?

NOTE- This Specialization Program is not for Beginners. This program is suitable for-

  • Those who have some basic understanding of Python.
  • And who has a basic knowledge of Linear Algebra and Machine Learning.

Interested to Enroll?

If yes, then check here- Deep Learning Specialization.

2. Generative Adversarial Networks (GANs) Specialization

Provider- deeplearning.ai

Instructor- Sharon Zhou, Eda Zhou, Eric Zelikman

Rating- 4.7/5

Time to Complete- 3 months ( If you spend 8 hours per week)

A generative Adversarial Network (GAN) is a powerful algorithm of Deep Learning. Generative Adversarial Network is used in Image Generation, Video Generation, and Audio Generation. In short, GAN is a Robot Artist, who can create any kind of art perfectly.

And in this Generative Adversarial Networks (GANs) Specialization, you will learn how to build basic GANs using PyTorch and advanced DCGANs using convolutional layers.

You will use GANs for data augmentation and privacy preservation, survey GANs applications, and examine and build Pix2Pix and CycleGAN for image translation.

There are 3 courses in this Specialization program where you will gain hands-on experience in GANs. Now, let’s see all the 3 courses of this Specialization Program-

Courses Include-

  1. Build Basic Generative Adversarial Networks (GANs)
  2. Build Better Generative Adversarial Networks (GANs)
  3. Apply Generative Adversarial Networks (GANs)

Extra Benefits-

  • You will get a Shareable Certificate and Course Certificates upon completion.
  • Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • Those who have a working knowledge of AI, deep learning, and convolutional neural networks. And have intermediate Python skills plus familiarity with any deep learning framework (TensorFlow, Keras, or PyTorch).
  • You should also proficient in basic calculus, linear algebra, and statistics.

Interested to Enroll?

If yes, then You can Sign Up here.

3. Neural Networks and Deep Learning

Provider- deeplearning.ai

Instructor- Andrew Ng, Younes Bensouda Mourri, Kian Katanforoosh

Rating- 4.9/5

Time to Complete- 20 hours

This course is the part of Deep Learning Specialization program. And I think this is the best course to begin your deep learning journey.

In this course, you will understand the major technology trends driving Deep Learning, key parameters in a neural network’s architecture, how to build, train, and apply fully connected deep neural networks, etc.

Extra Benefits-

  • You will get a Shareable Certificate.
  • Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • Those who have basic understanding of machine learning.

Interested to Enroll?

If yes, then You can Sign Up here.

4. TensorFlow 2 for Deep Learning Specialization

Provider- Imperial College London

Instructor- Dr. Kevin Webster

Rating- 4.9/5

Time to Complete- 4 Months( If you spend 7 hours per week)

In this specialization program, there are 3 courses where you will gain fundamental concepts to build, train, evaluate, and make predictions from deep learning models.

Along with this, you will learn TensorFlow to develop fully-customized deep learning models and workflows for any application. You will also learn TensorFlow APIs to include sequence models.

In the last course, you will learn how to build probabilistic models with TensorFlow and how to use the TensorFlow Probability library.

Now, let’s see all the 3 courses of this Specialization Program-

Courses Include-

  1. Getting started with TensorFlow 2
  2. Customizing your models with TensorFlow 2
  3. Probabilistic Deep Learning with TensorFlow 2

Extra Benefits-

  • You will get a Shareable Certificate and Course Certificates upon completion.
  • Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • Those who are familiar with Python 3, machine learning concepts, Probability and statistics, and basics of deep learning.

Interested to Enroll?

If yes, then You can Sign Up here.

5. DeepLearning.AI TensorFlow Developer Professional Certificate

Provider- deeplearning.ai

Instructor- Laurence Moroney (leads AI Advocacy at Google)

Rating- 4.7/5

Time to Complete- 4 months ( If you spend 5 hours per week)

Tensorflow is one of the most popular open-source Deep Learning libraries. It is designed to perform both numeric and neural network-oriented problems.

In this Certificate program, you will learn applied machine learning skills with TensorFlow to build and train powerful models.

There are 4 courses in this certificate program, where you will learn to build NLP systems using TensorFlow, handling real-world image data, and strategies to prevent overfitting, including augmentation and dropout. There are 16 Python programming assignments throughout the certificate program.

Now, let’s see all the 4 courses of this Specialization Program-

Courses Include-

  1. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  2. Convolutional Neural Networks in TensorFlow
  3. Natural Language Processing in TensorFlow
  4. Sequences, Time Series and Prediction

Extra Benefits-

  • You will get a Shareable Certificate and Course Certificates upon completion.
  • Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • This is Intermediate level program, some previous knowledge in Machine learning and in Python is required.

Interested to Enroll?

If yes, then You can Sign Up here.

6. Advanced Machine Learning Specialization

Provider- National Research University Higher School of Economics

Rating- 4.5/5

Time to Complete- 10 months (If you spend 6 hours per week)

This Specialization series is an advanced series of courses. If you want to learn more than the basics of Machine Learning, then this is the best choice for you.

This specialization program fills out all the gaps in your knowledge in Machine Learning. As this is an advanced series of courses, that’s why you need to have more math knowledge. In short, this specialization program is for those who are already in the industry. This course will sharpen their skills.

Throughout this Specialization program, you will create several projects, that will help you to build a more powerful portfolio.

This Specialization Program contains 7 Courses. Let’ see all these courses-

Courses Include-

  1. Introduction to Deep Learning
  2. How to Win a Data Science Competition: Learn from Top Kagglers
  3. Bayesian Methods for Machine Learning
  4. Practical Reinforcement Learning
  5. Deep Learning in Computer Vision
  6. Natural Language Processing
  7. Addressing Large Hadron Collider Challenges by Machine Learning

Extra Benefits-

  • You will get a Shareable Certificate.
  • You will get a chance to work on a wide variety of real-world problems like image captioning and automatic game playing.
  • Along with that, you will get a chance to take advice from Top Kaggle machine learning practitioners and CERN scientists.

Who Should Enroll?

  • Those who have Intermediate level knowledge in Machine Learning.
  • Or the one who is already in the industry and wants to sharpen Machine Learning skills.

Interested to Enroll?

If yes, then You can Sign Up here.

7. Introduction to Deep Learning

Provider- National Research University Higher School of Economics

Rating- 4.6/5

Time to Complete- 34 hours

This course is the part of Advanced Machine Learning Specialization program. In this course, you will learn the fundamentals of modern neural networks and their applications in computer vision and natural language understanding.

This course will teach you all the important building blocks of neural networks including fully connected layers, convolutional and recurrent layers.

There is a project associated with this course, where you will implement a deep neural network for image captioning which solves the problem of giving a text description for an input image.

Extra Benefits-

  • You will get a Shareable Certificate.
  • Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • Those who have basic knowledge of Python, and linear algebra and probability.

Interested to Enroll?

If yes, then You can Sign Up here.

And here the list ends. I hope these Best Deep Learning Courses on Coursera will definitely help you to learn Deep Learning at your own pace. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover all the Best Deep Learning Courses on Coursera. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

NOTE- Some of the links in the post are Affiliate Links. This means if you click on the link and purchase the course, I will receive an affiliate commission at no extra cost to you😊.

If you find these resources helpful, kindly 👏

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Aqsazafar
Aqsazafar

Written by Aqsazafar

Hi, I am Aqsa Zafar, a Ph.D. scholar in Data Mining. My research topic is “Depression Detection from Social Media via Data Mining”.

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