There is only one reason why you landed on this article*. You’re on the fence about whether to buy or take Andrew Ng’s most popular course in the world, namely Deep Learning Specialization.
In this article, I will be reviewing Deep Learning Specialization which I have been following over two months ago (to be calculated from the release of this article).
Before we get started though, here’s one very important thing you need to do: DO NOT BUY THE SPECIALIZATION if you haven’t read the entire article first.
Is that okay?
Then we can get started. I promise to be as comprehensive as possible and not leave anything out. That way you can decide whether to buy and pursue the residency without you having any doubts.
*You may actually have even landed on this article not knowing about this training path, but nonetheless wish to know what it is.
First, why pursue residency?
Andrew Ng in addition to being the founder of Coursera (the platform that hosts the course), is also the founder of DeepLearning.ai. One of the things that distinguishes this course from other courses is the passion that Andrew Ng puts into transmitting in the clearest way possible, the concepts that he applies in the field.
The Deep Learning specialization is one of his most famous (per)courses because, in addition to the clarity of the concepts conveyed, it is one of the most comprehensive ever seen to date.
If you want to pursue this specialization, I recommend first taking his course on Machine Learning or if you are not yet familiar with these disciplines, I recommend this guide on how to study artificial intelligence in 2021.
Why buy the specialization and what it includes
Specialization should be purchased because it gives you very competitive advantages over someone who only follows it in audit mode.
Let’s take a look together at some of the reasons why you should buy the specialization (later I’ll tell you the price and a little method to save money – totally legit – that I used):
- Mentality: our brain unfortunately works in a somewhat twisted way. It doesn’t place much value on something when we get it without having made the slightest effort. So if we take the course totally free we will commit less energy to following it and applying it.
- Quizzes: by purchasing the course you will be able to repeat each chapter thanks to the quizzes that will serve for your final evaluation.
Why is it good to take quizzes at the end of each chapter?
Taking quizzes at the end of each chapter will help you memorize even better the things you learned while studying the chapter.
- Practical projects: these are one of the best things that can be in an online course today. These are real guided exercises that help you better understand the theoretical concepts by applying them to practice.
Each project is tailored to each chapter, so you won’t have to waste time looking for projects to practice on that specific topic.
Finally, one of the things I liked the most is that for each code step there is an explanation that helps you understand even better what you are doing.
- Community: if you have any difficulties, doubts or questions there is an entire worldwide community ready to help you. I found it really useful when I encountered problems on a project!
- Certification: I think we can make this one part of the benefits of the purchase. At the end of all the specialization you will get a certificate that certifies worldwide that you have acquired these skills both theoretical and practical.
Deep Learning Specialization on Coursera: how much does it cost?
It depends. Yes you got it very right. It depends on how long you take to study, the more time you spend studying, the more you’ll pay for your residency subscription.
Depending on the person this can be an advantage or a disadvantage. It’s up to you to decide if you’re better off making the purchase at a time when you’re more free or not.
However, if you urgently need to follow it, do not get lost in chatter because in the end the cost is negligible for what it is actually worth such a course (later I’ll tell you how much I paid).
What does Andrew Ng’s Deep Learning specialization consist of?
It’s called specialization because it’s not a single course, it’s a set of 5 courses that introduce you to the big world of Deep Learning. Each course has a specific purpose and helps you better understand that particular topic.
In turn, the courses are divided into 3-4 “weeks” and each of these “weeks” has video lessons, quizzes and projects (or rather “LAB” – laboratories). Finally, unlike the course on Machine Learning, here we also have interviews with industry experts who study and practice the subject of Deep Learning for many years.
But so what are these courses?
Here is a list of the 5 courses included in the specialization:
- Neural Networks and Deep Learning: In this first course you will study the fundamental concepts of neural networks and DL.
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: you will open the black box of Deep Learning to understand the processes that drive performance and generate good results in a systematic way.
- Structuring Machine Learning Projects: you will learn how to build a successful machine learning project and practice decision making as a machine learning project leader.
- Convolutional neural networks: you’ll understand how computer vision has evolved and learn about its applications such as autonomous driving, face recognition, radiological image reading and more
I wrote an article on what convolutional neural networks are.
- Sequential patterns: you’ll become familiar with sequential patterns and its applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more.
If you would like more information about what you will learn at the end of each course, you can go to the specialization page in the “Courses” section.
For your information, the courses can be purchased individually. The problem is that by purchasing them individually, you will not be eligible for final certification of the entire specialization (I have included the links in the list titles).
How to follow the specialization: my experience
You may be wondering how I myself studied and how long it took me to go through the entire residency. Before I tell you that, though, I want to point out a mistake I made.
As you know the courses can be taken in audit mode, without you making the purchase. At first I did just that. I had started taking the courses completely free of charge only then I was faced with a problem. The mindset.
In fact, as I told you earlier, when we purchase something or get it with more effort we perceive more value for that particular thing.
Here I hadn’t considered it.
So after taking a break for a few days and evaluating the various benefits of specialization done on Coursera (described above), I decided to purchase it.
To complete all 5 courses and finish the entire “Specialization” took me a month and a week studying every morning with only two days off during the week.
Having been in residency for a month or so, I paid around 45 euros ($50).
But how did I only pay for one month and not two since it took me a little longer?
I simply took advantage of the 7-day trial. I’ll explain how.
Before I even started the trial, I watched all of the video lessons from the first and two “weeks” and started the free trial after that. This gave me more time to take advantage of the entire month’s subscription (I am charged on the eighth day after the trial begins).
One piece of advice I would give you is to follow Andrew Ng’s closely and take time to learn by incorporating breaks during the week.
But what to do once all the Deep Learning Specialization is over?
Once you’ve finished all 5 courses remember to deactivate your subscription (it’s automatic, so even if you’ve finished they may charge you another payment).
Here are the steps for deactivation:
- Click in the upper right hand corner on your name;
- “My purchase;
- “Deactivate subscription.
WARNING: When you have deactivated it, you will no longer be able to access the quizzes and exercises, so if you want to keep the projects to yourself, remember to download them once you have completed them!
I still, to repeat, review a few lessons from the course completely free of charge. For those there is no need to reactivate the subscription .
I hope this review was helpful in clearing your mind and gaining a better understanding of what Andrew Ng’s Deep Learning Specialization is. For your convenience, I’ll leave you the link to the specialization page here.