You want to be a data scientist. Maybe you have already begun your training towards the purpose or need a kickstart into the career. Regardless, AI and Deep Learning can be your entryway into the field. To ensure a successful journey, picking the correct deep learning course, with accurate knowledge and training, plays a pivotal role.
With the advancement in AI, the complexity of the problems will also increase. Fortunately, Deep Learning can help solve even the most challenging problems associated with AI.
Once a domain for Ph.D.s and researchers, today, Deep Learning sees mainstream application because of its diverse availability and practical application. Consequently, there is also a noted surge in the demand and the resultant job salaries for deep learning professionals and data scientists.
However deep learning is a vast domain. To dominate this area, you must acquire a global but clear vision of the subject. For this, you need to get access to the proper training, and with this guide, we will help you find one of the best deep learning courses.
Top Six Courses to Learn Deep Learning
- Deep Learning Specialization – Offered by DeepLearning.AI – [Coursera]
- Deep Learning A-Z™: Hands-On Artificial Neural Networks – [Udemy]
- Deep Learning with Python and PyTorch – Offered by IBM – [edX]
- Professional Certificate in Deep Learning – Offered by IBM – [edX]
- Deep Learning – [Udacity]
- Deep Learning – Stanford School of Engineering – [Stanford Online]
Course Selection Criteria
It took us days of research to shortlist the six deep-learning training programs. We compared them on three factors:
- Number of enrollments in the class
- A curriculum that was complete
- Programs that assure a bang for your buck
- Courses with the most prolific and trained educators
So, you can rely on our findings, and make your pick. Let us list down the deep learning certification classes one by one.
The Best Of Deep Learning Online Courses
1. Deep Learning Specialization – Offered by DeepLearning.AI – [Coursera]
Instructor | Andrew Ng, Kian Katanforoosh, and Younes Bensouda Mourri |
Live Instructor Led/Pre-recorded classes | Pre-recorded |
Course Rating | 4.9 stars from 125,432 ratings |
Enrollments | 707,654 students |
Free/Paid | Paid |
Certification | Yes |
Duration | Approximately 5 months to complete at a suggested pace of 9 hours/week |
Lifetime access | No |
Refund | If you subscribe, you get a 7-day free trial. After this, there is no refund, but you can cancel your subscription anytime. |
Is financial aid available? | Yes |
At the top of this list is the Coursera deep learning specialization that lets you train and create neural networks, implement them, find the primary architecture parameters, and incorporate deep learning into applications.
In addition, you will also know how to build a CNN, create and train RNNs, train test sets, employ optimization algorithms and standard techniques, and more.
In this deep learning training module, you will understand the challenges, capabilities, and consequences of deep learning, which offers an edge in your knowledge of AI technology.
There are 5 Courses in this Specialization:
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization, and Optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
Why should you choose this course?
- It is the best deep learning course because twenty-eight percent of students who took the class began a new career after finishing it, and eleven percent received a promotion or a pay hike.
- The instructors offer vital carer advice, which can prove instrumental in making a career in deep learning.
Things you may not like
- There is no refund policy.
- You will find repetition in different sub-courses as they are a part of the same specialization. A little overlap – that’s all!
Prerequisites
It is one of the intermediate-level deep learning online courses. For this class, you must possess:
- Python skills
- Understanding of if/else statements, for loops, basic programming, and data structures
- Fundamental knowledge of Machine learning and linear algebra
2. Deep Learning A-Z™: Hands-On Artificial Neural Networks – [Udemy]
Instructor | Ligency I Team, Kirill Eremenko, Hadelin de Ponteves, and Ligency Team |
Live Instructor Led/Pre-recorded classes | Pre-recorded classes |
Course Rating | 4.6 from 41,004 ratings |
Enrollments | 340,428 students |
Free/Paid | Paid |
Certification | Yes |
Duration | 22.5 hours of on-demand video |
Lifetime access | Yes |
Refund | 30-Day Money-Back Guarantee |
Is financial aid available? | No |
It is one of the detailed deep learning online courses. As part of this program, you will learn about the intuition behind artificial neural networks, recurrent neural networks, and convolutional neural networks and their application. You will also know how to apply AutoEncoders, Self-Organizing Maps, and Boltzmann Machines.
The whole deep learning training has two volumes that depict the two branches of Deep learning – Unsupervised and Supervised Deep Learning. Every section takes you through three different algorithms that simplify the learning mechanism. The instructor is responsive and will offer constant support across the class.
Why should you choose this course?
It is one of our top-recommended deep learning online courses because of the following reasons:
- It is a hands-on class that takes you through the Why behind the why of things.
- The instructor incorporates intuition tutorials that help you understand the techniques at an instinctive level.
- There is an abundance of coding practices to assess your learning.
- You will work on real-world datasets in this.
Things you may not like
- Some sections lack the intensity they deserve.
Prerequisites
It is Udemy’s best deep learning certification, but the class requires familiarity with an elementary Python programming language and high school mathematics.
3. Deep Learning with Python and PyTorch – Offered by IBM – [edX]
Instructor | Joseph Santarcangelo |
Live Instructor Led/Pre-recorded classes | Pre-recorded |
Enrollments | 43,928 students |
Free/Paid | Free |
Certification | Only if you opt for the paid version |
Duration | 6 weeks at a suggested pace of 2–4 hours per week |
Lifetime access | If you opt for the paid version |
Is financial aid available? | Yes |
It is the second part of the two-part series on how to develop Deep Learning models using Pytorch. You can take this specific course or take up the entire certificate program listed right after this one.
While the first part here takes you through the PyTorch basics, in this deep learning training, you will learn about building deep neural networks in PyTorch. Further, you will also study training the models with cutting-edge methods.
In this class, you will learn to train and build a multiclass linear classifier in PyTorch and apply knowledge of Deep Neural Networks and related machine learning methods. Also, introduction to CNN, dimensionality reduction, and autoencoders are vital discussion topics.
Why should you choose this course?
It is the best deep learning certification backed by IBM, and learners who complete it earn a skill badge – a verifiable, detailed, and digital credential that validates your knowledge and skills from the class.
Prerequisites
It is an intermediate-level class. You can make the most of this bestselling deep learning course if you are familiar with PyTorch Basics.
In addition, you should also have a hands-on understanding of Machine learning. If you lack this knowledge, you can enroll in the PyTorch Basics for Machine Learning before commencing the class.
4. Professional Certificate in Deep Learning – Offered by IBM – [edX]
Instructor | Alex Aklson, Aije Egwaikhide, Romeo Kienzler, Saeed Aghabozorgi, Samaya Madhavan, and Joseph Santarcangelo |
Live Instructor Led/Pre-recorded classes | Pre-recorded |
Free/Paid | Paid |
Certification | Yes |
Duration | 7 months at a suggested pace of 2 – 4 hours per week |
Lifetime access | No |
Is financial aid available? | Yes |
Next on our list is another best deep learning certification programs presented by IBM again – a complete package.
In this class, you will discover the elementary concepts associated with deep learning, develop an understanding of different neural networks, and build, deploy, and train various kinds of deep architectures, such as RNN, CNN, and Autoencoders.
After this, you will also study the application of deep learning in real-world situations.
It is one of the best deep learning courses to employ popular deep learning libraries like Tensorflow, PyTorch, and Keras for industry situations. There are six skill-building courses in this class.
Why should you choose this course?
- In this program, you will gather all the knowledge and skills to become a successful AI practitioner and commence a career in Deep learning.
- It is a hands-on deep learning certification wherein you will practice your Deep Learning skills via various projects, assignments, and hands-on labs, inspired by real-world data sets and problems from the industry.
What you might not like?
It is a professional certification program in AI and hence quite expensive.
5. Deep Learning – [Udacity]
Live Instructor Led/Pre-recorded classes | Pre-recorded |
Free/Paid | Paid |
Duration | 4 months at a suggested pace of 10 hours per week |
In Udacity’s AI Programming with Python Nanodegree program, you will study Numpy, Pandas, and Jupyter notebooks. In this session, the instructor will take you through cutting-edge topics, such as convolutional neural networks, neural networks, generative adversarial networks, and recurrent neural networks.
Prerequisites
For this deep learning course, you require a familiarity with the following topics:
- Derivatives
- Numpy, Pandas
- Jupyter notebooks
- Linear Algebra
- Intermediate Python
6. Deep Learning – Stanford School of Engineering – [Stanford Online]
Stanford needs no introduction. In their deep learning training, you will understand how to lead a successful machine learning project and create a neural network.
In addition, you will also study the Adam, CNN, RNN, Dropout, LSTM, Xavier/He initialization, BatchNorm, and more. You will learn about the various techniques to improve neural networks. These include regularization and optimizations, hyperparameter tuning, and deep learning frameworks (Tensorflow and Keras.).
It is a hands-on deep learning course with multiple case studies from different domains like hospitals and healthcare systems, autonomous driving, music production, and sign language reading.
Hence, the class teaches you the theoretical aspects and the practical industry application of deep learning concepts. You will implement all the ideas in TensorFlow and Python that you will also cover in this lecture.
Why should you choose this course?
- You will find several creative ways to apply your knowledge in this course.
- It has multiple assignments and quizzes to help you assess your learning from the class.
- The class has an open-ended final project to help you get a real-industry experience.
Prerequisites
Some prerequisites associated with this deep learning course are:
- Familiarity with programming in Python
- Understanding of Linear Algebra (matrix/vector multiplications)
To Sum Up..
So, these are the best deep learning online courses. It took us intensive research and study to pick these classes, and we can assure you that they are all top-notch classes, each better than the other. But, of course, you need to pick one to begin your journey in the field.
The Deep Learning A-Z™: Hands-On Artificial Neural Networks – [Udemy] can be a good pick. It is vast, has good reviews, offers deep learning certification, comes with lifetime access, has a responsive instructor, and provides ample instruction at a reasonable cost.
Frequently Asked Questions
Ques 1. Which career options are there in deep learning?
Ans. A deep learning professional can opt for a career as a software engineer, research analyst, Data Analyst, Data Engineer, Bioinformation, Software developer, etc.
Ques 2. What is the average salary for a deep learning engineer?
Ans. On average, a professional who underwent deep learning training and is certified to practice in the field earns $142,566 annually in America.