When it comes to artificial intelligence, deep learning courses have a lot of scope for software engineers who are willing to ace in this field. However, deep learning has a lot of competition, and mastering deep understanding in Ai or ML is a great thing one can ever do for his future. Isn’t it exciting to create self-driving cars with deep learning? The value of this automated technology has skyrocketed since Elon Musk has recently introduced a robot AI that could do any of our repetitive, boring jobs. Isn’t it exciting to be a part of the revolution? Moreover, deep learning can also help you recognize objects using computer vision techniques or talking and understanding human speech using natural languages processing techniques such as Siri and Google assistance.
In this article, I have enlisted the top 10 courses which would help you master deep learning. However, I have stuck to courses from Coursera since it offers the best courses on deep learning, and it is one of the best educational platforms on the internet.
1. Deep Learning Specialization
Offered by Deep Learning.AI, this course has a lot of credibility. Get ready to become a machine learning expert. This is one of the popular courses with more than 600000 students. This course is not applicable for beginners since it is necessary to know the basic python programming language. It will take approximately 5 months to complete this program.
Throughout this course, you will build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data. The course is instructed by the co-founder of Coursera itself- Andrew Ng, founder of deep elarning.ai. DeepLearning.AI is an education technology company that develops a global community of AI talent.
2. Neural Networks and Deep Learning
With nearly a million students enrolled for this course, Neural Networks and Deep Learning is a great course to learn about neural networks, backpropagation, python programming and it is just a small program with just 24 hours of duration. You have to learn a lot of linear algebra and ML.
Younes Bensouda Mourri and Kian Katanforoosh have collaborated with Andrew NG for this extraordinary program that would help you learn the foundational concepts of deep learning. The program will help you l; earn the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology
3. DeepLearning.AI TensorFlow Developer Professional Certificate
This is not yet another deep learning.AI course. DeepLearning.AI TensorFlow Developer Professional Certificate is primarily focused on TensorFlow tools. Tensorflow is a popular open-source machine learning framework to train a neural network for computer vision applications.
It is also an intermediate level course which gives you a step by step approach towards learning these subjects. Moreover, the highlight of this course is it will simultaneously prepare you for the Google TensorFlow Certificate examination. This is the best hands-on experience program on Tensorflow and this course is instructed by Laurence Moroney, who is a lead AI Advocate of Google. Don’t worry this is not yet another Andrew NG program.
4. TensorFlow 2 for Deep Learning Specialization
The TensorFlow 2 framework is very popular for deep learning. This course is for professionals, ML researchers, and even students. This is a long step-by-step program since it has a duration of 4 months to complete. It can only be completed in 4 months if you learn the program at a pace of 7 hours per week.
To make the best out of this program you should have a Specialization in python 3, general machine learning and deep learning concepts, and a solid foundation in probability and statistics. The course comes with project completion to get hands-on experience on the subject. Dr. Kevin Webster offers this program from Imperial College of London.
5. Advanced Machine Learning Specialization
If you are a person who gets easily bored if the program is offered by the same instructor, this is the right course for you. With 21 top-rated instructors compiled, this program has been offered to you. All the instructors are industrial specialists from the HSE University’s faculty of computer science.
The course is offered by HSE University which is one of the top-class universities in Russia. the course can be completed in a 10 month period and mind you, this course is only applicable for advanced AI learners. It is designed for individuals who are already in the industry. This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision, and Bayesian methods.
6. IBM Machine Learning Professional Certificate
Offered by IBM, this course is highly recommended. This course is tailor-made for students who are looking to develop a career in machine learning. Starting from Unsupervised Learning, Supervised Learning, Deep Learning, to Reinforcement Learning, you will learn every single ML subject.
Although this is supposed to be an intermediate program, you can enroll for this if you have some basic knowledge of computer skills like leveraging data. The program is offered by the best minds of IBM- Mark J Grover. Under the IBM data and AI learning topic, he is the Digital Content Delivery Lead for IBM.
7. Generative Adversarial Networks (GANs) Specialization
Generative Adversarial Networks (GANs) Specialization is yet another program offered by Deeplearning.AI. instead of learning overall AI, it is better to stick to a particular topic so that you can master it. Generative Adversarial Networks (GANs) are powerful machine learning models capable of generating a realistic image, video, and voice outputs.
This is an exciting program that will help you build your own model using Pytorch. The program is instructed by Sharon Zhou. She is a lead Instructor of Coursera and she is in the Department of Computer Science at Stanford University. The course can be completed in a 3month span of time.
8. An Introduction to Practical Deep Learning
We have come across a lot of courses on deep learning but what stands out this course is one- it is offered by the great INTEL itself. Two- this course will give you a completely practical approach towards learning about deep learning and you will not be learning through the same mediocre lectures.
All the topics are covered by giving a practical understanding of the making of self-driving cars, speech interfaces, genomic sequence analysis, and algorithmic trading. The highlight of this program is it is offered by Andres Rodriguez who is the Sr. Principal Engineer of INTEL. It is a short and crisp program that can be completed within 17hours.
9. Climate Change Forecasting Using Deep Learning
Well, I know you should have kinda got fed up by now seeing the same deep learning courses. Now I have suggested something different from the previous courses. Climate Change Forecasting Using Deep Learning is not a course precisely. It is a project-based program that would help you improve your analytical skills.
If you are not looking for a course this is the right pick for you. Some people already know the subject matter of AI but want some practical knowledge, you can pick this project which is guided throughout the end of the program. This project will help you understand the theory and intuition behind Recurrent Neural Networks and LSTM. It is just a one-hour intermediate program.
10. Machine Learning Specialization
With over 1,70000 students, Machine Learning Specialization is a great program with a lot of guided information. It is a long program which can be completed within 7 months if you study this course for 3 hours per week. You will not only stick to deep learning, but you will also get a general idea of ML subjects.
The program is offered by leading researchers from the University of Washington. The lead instructor of this program is Emily Fox. She is an Amazon Professor of Machine Learning. The credibility of the course is pretty high since the certification is offered by the University of Washington. You will also cover the subjects in ML-like Prediction, Classification, Clustering, and Information Retrieval.