5 Effective Websites and Tools to Learn Artificial Intelligence

Probably the most popular and demanded direction in IT now is the development and support of artificial intelligence. Beginners became especially interested in this direction after the advent of ChatGPT, and they can be understood. The field is really interesting and has a great future.

In our opinion, this is one of the most difficult areas to start your IT career - the initial requirements for a Junior specialist are very high, and the competition is just crazy. Nevertheless, if you decide to do this, it means that you are clearly not afraid of anything, which means that you are ready to learn and learn everything in order to get a dream project. We have prepared for you today a list of resources that would help you get a position as a Junior Specialist in this field. This is general and basic knowledge that will be useful to you in any case, no matter what area of ​​artificial intelligence you will work in. Enough talking, let's get started.


If you can apply for the position of a developer without knowing the multiplication table, then I don’t know, for example, mathematical statistics or linear algebra, you won’t be able to get a job even as a Junior AI specialist. No matter what anyone tells you, math should always be your first step towards your dream project. Those who say the opposite are wrong.

There are a lot of math resources, but I would recommend Khan Academy. First, it's free. Remember, to get a Junior specialist position in any field, you do not have to pay a dollar, all the resources for this are free. Secondly, there is just a huge variety of math courses, ranging from high school math to college math courses.

Khan Academy - Statistics and Probability

Khan Academy - Statistics and Probability (source)

I would recommend that you pay attention to the course of mathematical statistics and probability theory. It is quite large and detailed. Here is excellent material not only for a beginner in the field of AI, but also in general an excellent knowledge base for those who in one way or another have encountered working with big data.

There are other math courses on the site, but to be honest, it all depends on you and your preferences. In my opinion, a course in mathematical statistics is quite enough for a Junior position, but if you feel that somewhere you have gaps in knowledge, then it is worth filling these gaps with other mathematical courses on this site.

Elements of AI

When we have got a sufficient mathematical base, we can move on to the basics of AI. Elements of AI will help us a lot with this. The courses here are also free and cover all the questions you've ever asked yourself about artificial intelligence.

When I took courses here, I treated them not as courses, but as a source of answers to all my questions. I had a general idea of ​​how AI works, what its work is based on, but I didn’t know the details and didn’t even know about them. In general, this course answered many of my questions and I received the same basic theoretical knowledge.

Elements of AI - Theory Page

Elements of AI - Theory Page (source)

Treat this resource not as a course, but as a book, because in fact this is a book with beautiful pictures. On the site you will find two parts - theory and practice (AI building). As I said, the theoretical part is a book, where, by the way, there is a lot of material that will last for months of training. The practical part also includes a lot of theory, but is more focused on small exercises, where you will build simple neural networks on your own and create your own primitive AI.

The resource is excellent, and the material is presented very clearly. Sometimes it seemed to me that even a child would be able to understand part of the material. I highly recommend at least getting acquainted with the theory, because the practice is only ahead of us.


If you are interested in AI and machine learning, it is logical to assume that you know at least the basics of the Python programming language. This is the most popular language that you would have to work with and almost the only one (if you don't know Python, don't worry, I'll talk about that a bit later).

This resource will upgrade our Python. In general, Kaggle is a resource for data scientists - analysts and Data Scientists. However, there is a huge amount of material that you and I may need. A machine learning course, for example (there are two of them - one for beginners and one more advanced).

Kaggle - Intro to Machine Learning

Kaggle - Intro to Machine Learning (source)

If at the previous stage, we received a theoretical basis, then here we learn to work with our hands and apply the knowledge gained in practice. I chose Kaggle because there is a huge space for practice here, since every day other users publish datasets of a very different nature and volume that we need for practice.

If the course seemed not enough for you, then you can go on a free voyage and apply the acquired skills on this course on the datasets of other users. Kaggle is a huge practice space, be sure to take advantage of it.


As promised, I write about Python in a separate part of the post. The fact is that Python is to you like a knife to a chef or an ax to a lumberjack. This is your tool, you get a bus ticket on the AI route. Without knowledge of Python, you will not even pass the first stage of selection.

We have written a lot about educational resources for learning Python and will not repeat here. Resources can be found here or on our resource finder. Here I want to mention HackerRank. This site as a whole is a great platform for learning and practicing hard skills and Python is no exception.

HackerRank - Python Page

HackerRank - Python Page (source)

The site has many of the shortcomings we've written about here, but it's still a great educational resource for all levels. The courses are divided by difficulty level and topics in such a way that anyone, even those who have drunk Python for the last time at school, can start learning and complete it successfully. Yes, here you will not get the skills to write algorithms for AI, but you will get the base and starting conditions for getting a Junior position and further training.


Working in the field of AI is a constant work in a large amount of data, I think it's stupid to argue with that. To work with a large amount of data, we will definitely need SQL. On our site, we write quite a lot about SQL. You can view our collections of educational resources at the link or in our resource finder at the link. Therefore, we will not dwell on this in detail.

But what we will dwell on in detail is on the DataLemur website. This is a site with entrance tests for interviews and test items from top companies in the US and the world. You can test yourself by imagining that you were interviewed by an HR specialist and Team Lead in the team of one of these companies.

DataLemur Start Page

DataLemur Start Page (source)

When interviewing for a Junior position in AI, you will sooner or later be given the task of writing a database query in SQL, and it would be nice to be prepared for this. This resource will prepare you for a variety of tasks and, most importantly, will prove to you how unusual and diverse test tasks can be. I highly recommend going through all the available test tasks on this site, you will not regret it.


I really hope that this article will become a motivation for you to learn, and not a trigger to stop trying and trying. You need to study a lot, but if you have the desire and motivation, then learning for you will be easy and fast. It is difficult to talk about the timing, because training is always individual, but I would say that on average, the program presented by us in this article will take from 4 to 6 months with daily classes.


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