The age of Deep Learning has arrived. Though Neural Networks trace their history back to a paper published in 1943, it had been forgotten in the labyrinths of time since not much could be done with it because of hardware and other limitations of the time. Then some researchers dusted off the concepts and applied them to newer and much more powerful hardware and optimization algorithms, allowing them to build deeper and denser neural networks with amazing results and applications.
Nowadays, not a day goes by without an announcement of yet another breakthrough in the field of Deep Neural Nets, say for example GPT-3, Whisper, DALL-E, and many others. Even Indian companies have seen the adoption of Deep Learning gaining traction in fields like Natural Language Processing, Computer Vision, etc. These emerging fields are going to see an uptick in demand and if you have had your hands dirty working in this field, you are very likely to be a hot cake for these tech companies.
So this brings us to the question of where to start. If you aspire to start learning Deep Learning, Coursera Deep Learning Specialization is a popular and recommended course. The instructor, Andrew Ng, is a very tall and respected figure in the AI & Deep Learning domain.
Almost anyone with a basic understanding of Python and Matrix operation can cover the ground without much of a hiccup. If you ever find yourself stuck or confused, the course gives you access to the deepleaning.ai community where you can have your doubts clarified.
Course Structure & What you are going to learn:
The entire course is divided into 5 modules which are further broken down into 4-5 weekly sprints. You can set your own pace of study and track progress. There is a deadline for the submission of weekly quizzes and assignments. But in case you can’t make it in time, don’t sweat. You can push the submission dates. But it’s recommended that if you have the time to complete the courses before time, do it since it could save you some bucks as it has a subscription-based model. The earlier you finish, the lesser you have to shelve out.
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The modules, taken as such from the site, are as under:
- Neural Networks and Deep Learning: In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. You will build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture, and apply deep learning to your applications.
- Improving Deep Neural Networks: In the second course, you will understand the processes that drive performance and generate good results systematically.
- Structuring Machine Learning Projects: In this module, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader.
- Convolutional Neural Networks: In this course, you will learn computer vision and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more.
- Sequence Models: This course familiarizes sequence models like RNN, LSTMs, etc., and their exciting applications like speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more.
How much time is it going to take?
Coursera suggests a 9 hours/ week of commitment and at this pace, it normally takes 5 months to cover the entire course as per their stats. But if you are willing to put in a few more hours, you could very well finish it off in 2 months or lesser.
What is the Cost?
The course is available on a subscription model at $49/month with a starting 7-day free trial period. But if you are pressed financially or a student who can’t afford this much, this course also has financial aid available. You just have to write a form detailing why you want to take this course, what outcomes you want to achieve and how much you can manage to pay when prompted. You may get free access for a specific period to the entire course depending on your application.
Course Ratings and Enrollments
This course has been immensely liked by the audience, with 1,124,253 enrollments till now and an aggregate rating of 4.9-star rating from a total of close to a quarter million reviewers which speaks volumes about the quality and utility of the program.
Does it suit your style of learning?
It depends. The course goes in a bit deep into the theoretical aspects of Deep Learning models. You also get to practice what you learned in the exercises.
You might want to put in additional practice outside of exercise labs provided by Coursera to get a firm grasp of concepts and learn how to apply the concepts. But rest assured, it is a great course for beginners. You might want to put your 7-day trial period to maximum use to see whether the course style is suitable for you.
Have a great Deep Learning experience!