Top 5 Deep Learning and Neural Network courses to learn in 2021

javinpaul
javinpaul
Sep 19, 2020 · 9 min read
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Deep Learning on Coursera by Andrew Ng

Hello guys, if you want to learn Deep learning and neural networks and looking for the best online course then you have come to the right place. Earlier, I have shared the best data science course, and today, I am going to share the best deep learning online courses from Udemy, and Coursera.

Learning Deep learning in-depth? Sounds recursive? No? It is, indeed. There is no doubt that Machine Learning is a tough subject, and in-depth knowledge, in particular, requires a lot of maths and complex terminology and very tough to master.

If the subject matter is that tough, then how do you learn it better? Well, choose a course that can explain this complex topic in simple words. We are actually blessed that we have many excellent instructors like Andrew Ng, @Jeremey Howard’s, and Kirill Eremenko on Udemy around who are not just the expert of deep learning but also excellent instructors and teachers.

I firmly believe that every programmer should learn about Cloud Computing and Artificial Intelligence, as these two will drive the world in the coming years. Data Science, Machine Learning, and Deep Learning are essential for understanding and using Artificial intelligence in many ways, and that’s why I am spending a lot of my spare time learning these technologies.

My Machine learning journey started a couple of years ago when I come to cross Andrew Ng’s excellent Machine Learning course on Coursera, It also happened to be Coursera’s first course as Andrew Ng is also one of the founders of Coursera.

More than the course, Andrew inspired me to learn about Machine Learning and Artificial intelligence, and ever since that, whenever I read him like on his Deep Learning course launch on Medium, I always get excited to learn more about this field.

Another story that inspired me a lot was of a Japanese farmer who used Google’s TensorFlow and Machine learning to filter and sort Cucumber on his farm, which apparently only his mother could do because of her years of experience.

Stories are compelling; they not just teach but also, inspire and you find them a lot in these excellent courses, which I am going to share with you about deep learning in-depth.

Btw, if you are new to Machine learning then don’t start with these courses, the best starting point is still Andrew Ng’s original Machine Learning course on Coursera. Only after you take that course, you should check these advanced courses to learn neural networks and deep learning in-depth.

5 Best Courses to Learn Deep Learning and Neural Network for Beginners

Without wasting any more of your time, here is my list of best courses to learn Deep learning in-depth. I have chosen courses that are suitable for both beginners and developers with some experience in the field of Machine learning and Deep Learning.

Even though Maths is an integral part of Deep Learning, I have chosen courses where you don’t need to learn complex Maths concepts, whenever something is required, the instructor explains in simple words.

1. Deep Learning Specialization by Andrew Ng and Team

Believe it or not, Coursera is probably the best place to learn about Machine learning and Deep learning online, and a big reason for that is Andrew Ng, who literally made Machine learning popular among developers.

If you don’t know, he is also one of the founders of Coursera, and his classic Machine learning course offered by Stamford is probably the first online course on Coursera.

Apart from that classic course, Andrew has created a couple of more gems like AI For Everyone, which is again I recommend to every programmer and non-tech guys.

AI is not just for programmers but for everyone, and this is the best course to learn AI for all non-technical people like project managers, business analysts, operations, and event management team.

Coming back to Andrew’s Deep Learning Specialization, which is a collection of five courses focused on neural network and deep learning, as shown below:

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

Andrew follows a bottom-up approach, which means you will start from the smallest component and move towards building the product. In these five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects.

Here is the link to join this course Deep Learning Specialization

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You will also learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing.

The course is not just about boring theories; it’s very hands-on and interactive. You will practice ideas in Python and in TensorFlow, which you will learn on the course.

The best part of the course is that you will hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice, which is very inspiring and refreshing.

If you are serious about deep learning, I strongly suggest you join this specialization and complete all five courses. It may take between 3 to 5 months, but it’s completely worth your time and more than 500K learners have already benefited from this specialization.

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

If you don’t have 3 to 5 months to spare but want to learn deep learning in detail, then you should join this course.

In this course, you will learn about how to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts: Kirill Eremenko and Hadelin de Pontes.

This course will teach you almost everything you need to know as a Deep learning expert, not in the depth of the previous session but still good enough. It covers a lot of ground from basic to advanced deep learning concepts like ANN and CNN concepts.

I really like the way Kirill shows the intuitive part of the models, and Hadelin writes the code for some real-life projects.

Talking about social proof, this course has been trusted by more than 170,000 students, and it has, on average, 4.5 ratings from close to 23K ratings, which is just amazing.

In conclusion, this is an exciting training program filled with intuition tutorials, practical exercises, and real-World case studies. I strongly recommend this course to anyone interested in Data Science and Deep Learning.

Here is the link to join this course online — Deep Learning A-Z™: Hands-On Artificial Neural Networks

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3. Introduction to Deep Learning

This is another impressive course from Coursera on Deep learning, didn’t I say that Coursera has the best Machine Learning course on the internet? Well, Yes, and this course is part of their Advanced Machine Learning Specialization.

The goal of this course is to give learners a basic understanding of modern neural networks and their applications in computer vision and natural language understanding.

The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. You will learn the basic building blocks of neural network and how it works layer by layer.

Here is the link to join this course Introduction to Deep Learning

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Though, it’s expected that you have good knowledge of Python and Maths. If you are not comfortable with Python yet, I suggest you take one of the top Python courses I have suggested before.

And, if you find Coursera courses, specialization, and certifications useful then I suggest you join the Coursera Plus, a great subscription plan from Coursera which gives you unlimited access to their most popular courses, specialization, professional certificate, and guided projects. It cost around $399/year but its complete worth of your money as you get unlimited certificates.

4. Practical Deep Learning for Coders by fast.ai

This is Jeremy Howards’s classic course on deep learning. He is another awesome instructor on the field of Deep Learning along with Andrew Ng of Coursera and Kirill Eremenko on Udemy.

Talking about his course, it’s just the opposite of Andrew Ng’s Deep learning course.

While the previous one takes a bottom-up approach, this course takes a top-down approach. I mean, you are first introduced to the product, and then you deep dive into individual parts.

The best part of this course I that it’s very well structured and moves step by step, which helps to build the complex deep learning and neural network concepts. There is also a book with the same title which you can buy on Amazon.

Here is the link to buy his book — Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD

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5. Data Science: Deep Learning in Python

This is another awesome coursera specizliation to learn Deep learning. This course provide the MOST in-depth look at neural network theory and how to code one with pure Python and Tensorflow.

If you ever wanted a course that can teach you how to create your own neural network from scratch, then this is the course you should join.

This course, you will get you started in building your first artificial neural network using deep learning techniques. You will also find an in-depth explanation of maths behind ANN, which is very important for data scientists.

The courses use Python and NumPy, a Python library for machine learning to build full-on non-linear. It will also teach you how to install TensorFlow and use it for training your deep learning models. I highly recommend this course to anyone who wants to know how Deep Learning really works.

Here is the link to join this courseData Science: Deep Learning in Python

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That’s all about some of the best deep learning online courses to master neural networks and other deep learning concepts. We have also learned useful Python libraries like TensorFlow, Pandas, and Numpy, which can help you with data cleansing, parsing, and analyzing for your deep learning models.

You can use any of these courses and online training to learn deep learning, but I highly recommend you to check Deep Learning specialization on Coursera by Andrew Ng and team. It’s by far the most comprehensive resource on deep learning.

If you like this article, you may like my other Python, Data Science, and Machine learning articles as well:

Thanks for reading this article so far. If you like these deep learning courses, then please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. — If you like to learn from free resources, then you can also check out this Deep Learning Prerequisites: The Numpy Stack in Python V2 free course on Udemy. More than 16K Students have joined this course and you just need an Udemy account to enroll in this course.

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javinpaul

Written by

javinpaul

I am Java programmer, blogger, working on Java, J2EE, UNIX, FIX Protocol. I share Java tips on http://javarevisited.blogspot.com and http://java67.com

Javarevisited

A humble place to learn Java and Programming better.

javinpaul

Written by

javinpaul

I am Java programmer, blogger, working on Java, J2EE, UNIX, FIX Protocol. I share Java tips on http://javarevisited.blogspot.com and http://java67.com

Javarevisited

A humble place to learn Java and Programming better.

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