Most likely your question was “How can I study artificial intelligence as a self-taught person?” or something like that.
Well you landed on the right article. In this guide, I will advise you how to study artificial intelligence in a smart and completely autonomous way by taking free and/or paid (low price) courses.
I wrote this guide because I, like you and many other people I’ve met, felt lost at the beginning of our journey. We didn’t know where to start and what was the right path to follow.
So I said to myself “Antonio there is a need to write a nice guide that can be of help to other people who will be starting in this industry”.
In this article, I will talk about how to best study artificial intelligence and recommend courses from which you can draw more knowledge, during your study.
Before you begin though, know that this guide will not specify what professions you can pursue with the courses you take. Once you’ve completed the course and are more knowledgeable you can decide for yourself which direction to take.
I won’t go into too much detail, I’ll try to make this guide as understandable and concise as possible, I promise!
P.S. Before you start anything read the article all the way through.
Are you ready?
…Let’s get started!
Studying artificial intelligence: My experience
To start and to be able to give you a better understanding of what’s to come, I’ll tell you what was and what is more, my experience.
If you arrived on this article, you surely know what artificial intelligence is and are interested in learning more about this discipline.
Well you need to know that it’s not simple. The field of artificial intelligence is more diverse than it may seem.
Don’t worry, I didn’t know that at first either.
As a novice, starting out, I got a general idea about AI. I took a free course done by Finland that serves to train young people on the subject. This short course was really well done and there are no overly technical notions, although…(we’ll get to that in a bit).
The course in question is called “Elements of AI“
After finishing this course, I continued to train online through free and paid sources.
For example, at the time I’m writing this article, after taking courses on Python programming, courses on machine learning and courses on deep learning, I’m continuing to delve into the field of computer vision because it’s the one that I currently enjoy the most.
Today, thanks to my experience in taking courses, I’m going to recommend what I think is the best one to start delving into the field of artificial intelligence.
Before I recommend the first course though, I want to make a few notes.
Why study Artificial Intelligence?
For some people, studying artificial intelligence is not entirely easy. It takes a lot of patience and a lot of determination.
I think studying artificial intelligence is one of the most eye-opening things I’ve done. It has allowed me to access knowledge that I didn’t have even before delving into this subject. It has allowed me to know what lies behind today’s technologies. But most of all, it has given me the opportunity to learn about its extreme and unlimited potential.
This technology is the present but it will mostly be the future. Whatever you see implemented in the world will have a piece of artificial intelligence built in from now on!
Artificial Intelligence is like salt. You can put it anywhere.Antonio Furioso – (yes I am quoting myself because the phrase is funny).
Then you can decide whether to take part in the change or devote yourself to something else.
And if you’re wondering: No, it’s not too late!
Although AI is a technology discovered long ago, its potential is only expanding today and will continue to do so in the coming decades.
So here’s why you should study Artificial Intelligence!
If you want to delve deeper into why to study artificial intelligence I have an article for you.
But what job opportunities can Artificial Intelligence offer you?
As I mentioned earlier, the AI field is really quite vast. Artificial intelligence can really be applied in every field, even the one you like the most.
Think about it!
“Okay, but what could I do once I’ve taken these courses and/or delved into one of the AI sub-fields?”
Well, there are many jobs that you can undertake by studying this discipline. Many of these jobs also, are paid really well to reach figures such as $140,000 in U.S.
What are some of these jobs? Here is a short list for you:
- AI Engineer
- Machine Learning Engineer
- Machine Learning Developer
- Data Analyst
- Computer Vision Engineer
- Data Engineer
- Data Scientist
- Computer Vision Developer
- Computer Vision Researcher
- Natural Language Processing Expert
- Natural Language Understanding Expert
- and much more…
But are there jobs where you don’t need to know how to program?
Programming doesn’t excite everyone and maybe not even you, which is why I have some good news you might like.
There are also jobs in this field where you don’t have to touch the programming language. Most of these professionals work with development and research teams, others only play a consulting and sales role.
Yes, it is really very nice if you are not a programming lover.
Despite this though, my advice is to study the field of programming because of what comes with it. However, a consultant with too general a foundation will never be a good consultant.
Now let’s get to the core of this guide and see the path you can follow to learn more about artificial intelligence and help change the world.
Because I want you to be aware of what you’re getting into, as you read and next to each link, I’ll put asterisks to indicate whether the course is
- FREE (*).
- is a paid course that you can take for free (***).
Also, at the end of the article, I’ll tell you why it’s important whether you take some of these courses for a fee or not.
P.S.S. For a better study follow the order of the article, otherwise, if a certain thing you have already studied or deepened skip that part.
Study Artificial Intelligence from the ground up
Just taking the Elements of AI course I recommended earlier won’t help you achieve your goals, it will only serve to give you a general idea of what AI is and its potential.
But I have to be honest, the Elements of AI course even though it helped me to get a general idea, a little bit confused me at the beginning and that’s why I later had to pick up some concepts again.
If you want you can take this free course at the same time as the rest of your course or you can decide to skip it if you more or less know what we’re talking about.
How to get started on your path?
To get started on this new path, what I recommend is to know a programming language. In this guide, the courses I will recommend use Python as the default language.
Python for me is one of the simplest languages there is in programming, although for many it may not be so. Also, this language, is the most used and supported by the Artificial Intelligence community.
Like many other languages it can be learned online and for free.
My advice is to learn it by following this course called Python for everybody *** (recommended to buy the specialization, not the single course) because besides being structured really well, it allows you to practice as you study the topic.
Otherwise, if you want to follow another way, you can study python for free and practice on your own by following these very practical tutorials* (study only the tutorials of the “Basics” and “Intermediate Python Fundamentals” sections) but keep in mind that you will have to look for the most suitable exercises for the specific topic yourself.
If you don’t hate them, you love them
What am I talking about in your opinion?
These two subjects you can’t avoid if you don’t like them. They are fundamental steps if you want to know artificial intelligence and its algorithms well.
Yes, I’m talking about math and statistics. But don’t worry, you don’t have to be knowledgeable about everything math and statistics.
WARNING: Before we get to the courses you need to take, I want to tell you that the above two subjects are really fundamental in the field of Artificial Intelligence.
Statistics is mostly applied to data visualization (which is very useful for predicting phenomena thanks to Machine Learning), while mathematics (or algebra) is key to understanding what’s behind the algorithms that are used in AI.
What are the sources where you can study these two subjects?
One of the best sources to draw these notions from is definitely Khan Academy*. This is one of the completely free and best-provided resources in science (mostly).
Unfortunately, however, it is not easy to recommend a path for you to follow. There are really a lot of courses on mathematics here, although very comprehensive.
That’s why here are some sources where you can study what you need even for free, taking the courses even in audit mode (click on the single course > “Enroll” > “Audit mode”).
To learn more about statistical concepts and its basics I recommend you to follow the YouTube videos made by the StatQuest channel, here is the playlist for statistics basics*.
Talking about algebra instead, the specialization: “Mathematics for Machine Learning “*** is suitable to give you the necessary knowledge to delve into mathematical concepts of machine learning.
Absolute advice: follow these courses carefully because many concepts will come in handy in life and in the applications of your algorithms.
We use what we have learned to visualize data
How to proceed after taking math courses for Machine Learning and Statistics?
Once you’ve taken the courses recommended so far, you can try your hand at the data visualization part.
This is where a Data Analyst is trained. His or her ability to be able to read data and know-how to translate it for the inexperienced is critical to a company.
In this case I absolutely recommend you to follow “Understanding and Visualizing data with Python “*** a course that allows you to know perfectly the theoretical notions and if purchased you could also do a lot of practice to better understand the theoretical concepts (I recommend the purchase).
Now before we get to the guide here’s one more piece of advice: take your time. Don’t try to rush things and get a good understanding of what you are doing.
Okay, we can proceed.
After you’ve taken the courses suggested so far we can move on to the algorithm creation part. Here you will have just as much to do, studying the different algorithms and understanding how they are composed.
Course on Machine Learning
We have already talked about it in some of our articles. Actually, the most interesting and curious part starts now.
By following these courses you will be able to learn the mechanism of the main Machine Learning algorithms and also apply them for real situations.
To study Machine Learning I can’t help but recommend you Andrew Ng’s very famous course “Machine Learning “***. This course is really structured for the best and its author, as well as founder of Coursera, explains in a really exceptional way putting a lot of enthusiasm and making many examples.
A note must be made here, however.
The course although it is really good, in some video lessons the audio is not exceptional there is a bit of background noise (obviously it is a very small flaw), also the programming language used is MATLAB.
So here is my advice for how to best study Machine Learning!
Take this course in “audit” mode (for free) to get a good theoretical knowledge but, after you have taken it, deepen your knowledge with this other course on machine learning with python*** .
By purchasing it, you will not only repeat and deepen certain concepts, but more importantly, you will be able to practice as you study.
Let’s go deeper: Deep Learning Courses
I don’t want to go on too long because before I finish I would like to give you some more advice that could be very useful.
So the last course I suggest you purchase in this guide is Andrew Ng’s Deep Learning Specialization**.
Unlike the course on Machine Learning, the audio is better. By taking this course myself, I realized how much knowledge I gained while studying.
By the time you get to this point (after you’ve taken all the courses), your mind will have been opened to new ideas and you’ll understand how the artificial intelligences that are being implemented in the world today really work.
Before you close: What to do after you’re done?
If I have written this guide, it is because I genuinely want to help those who are further behind me as a student.
At the beginning I made many mistakes before approaching this subject seriously. In fact I thought that by following the courses (very superficially) only theoretically I would become capable and skilled in the field.
Obviously I was wrong and had to start over. So here are what my recommendations are:
- Persevere until you understand something, it will be crucial during your learning.
- Give time to yourself to learn and assimilate the concepts you’ve studied. Don’t rush it.
- Don’t think that after taking these courses you will become an expert.
- …practice a lot and go over what is mentioned during the video lessons (especially the libraries).
To purchase the course or not?
As I told you when I first looked at the courses, I only wasted precious time because afterwards I had to pick up everything I had done up to that point.
When I realized my mistakes then, I started to give myself study goals and put myself there seriously.
Purchasing the courses not only allowed me to practice, but also gave me a commitment to continue what I was doing when I thought all of this wasn’t for me.
I highly recommend purchasing the suggested courses because they allow you to practice based on what was explained in the class.
It is very useful to assimilate the concepts better and by doing so you will save time in finding the right exercise to do at that moment, and money.
And then why not? They give you a certificate that is valid worldwide.
Some courses are on a monthly subscription, which means you pay based on how long it takes you to complete it. So once you’re done, remember to cancel!
Find your own study method, I used to take notes with pen and paper (because I assimilate better that way). Finally, whenever you finish a course, repeating and practicing consistently is the only way to get really good at it.
Choose your way!
After studying Deep Learning you could delve into both fields of Computer Vision and Natural Languages Process or specialize in just one and become a professional in that field.
I currently choose to specialize in Computer Vision and am practicing hard to become an expert in the subject.
That being said I thank you if you made it all the way through the guide and hope you found it very helpful!