Top 5 Deep Learning and Neural Network courses to learn in 2024
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, best Machine Learning Courses, and best AI courses, 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 is 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 experts 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 and DeepLearning.ai, the company behind Coursera’s most popular Deep learning program.
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 guy.
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 teams.
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
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 in 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
3. Introduction to Deep Learning [Coursera Best Course]
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 a discussion of stochastic optimization methods that are crucial for training deep neural networks. You will learn the basic building blocks of a neural network and how it works layer by layer.
Here is the link to join this course — Introduction to Deep Learning
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 it's completely worth your money as you get unlimited certificates.
4. Practical Deep Learning for Coders by fast.ai
This is Jeremy Howard’s classic course on deep learning. He is another awesome instructor in 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 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
5. Building Advanced Deep Learning and NLP Projects [Educative]
I’ve always been a huge believer in learning by doing. I think there’s real value in taking what you’ve learned, piecing it together, and building something and that’s why I like to learn from interactive courses like this text-based, interactive course from Educative.io, a new learning platform to learn in-demand tech skills.
As a machine learning engineer, you need to know things like which models to use for certain tasks, how they might improve training speed or model accuracy, and above all else, how to code machine learning models.
The last point is what I want to focus on: “how to code machine learning models”.
It’s one thing to know the calculus behind backpropagation and gradient descent, but it’s an entirely different skill to be able to build real-world machine learning models.
Employers love when you can show that you’ve worked on real projects. Particularly in interviews, you’ll get some great bonus points if you can show that you not only know what you’re talking about, but you have the experience to back it up.
So, in the spirit of building ML models and practical experience, I’d like to share with you a very exciting course: Building Advanced Deep Learning and NLP Projects
What I really liked about this course is that it's a project-based course. It will really get you used to building real-world applications using machine learning. You’ll work with all the tools of the trade like NumPy, Matplotlib, sci-kit-learn, and Tensorflow.
If you really want to get some practical experience with deep learning and NLP, then I highly recommend this course. Plus you’ll have some great additions to your portfolio.
Here is the link to join this course — Building Advanced Deep Learning and NLP Projects
And, if you find the Educative platform and their interactive courses useful then you can also get an Educative Subscription that provides access to not just this course but their 210+ courses in just $14.9 per month. It’s very cost-effective and great for preparing for coding interviews
6. Data Science: Deep Learning in Python
This is another awesome online training course to learn Deep learning. This course provides 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 will get you started in building your first artificial neural network using deep learning techniques. You will also find an in-depth explanation of the 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 course — Data Science: Deep Learning in Python
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 the 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:
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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.
