You are unlikely to be a visual learner. Or auditory. Or any of the four that are generally accepted to be true. Even though this division sounds plausible (and a cool excuse for not understanding something), there is no strong scientific evidence for it being true on a mass scale. Whenever you have a lunch break please watch the video from Veritasium about this, or do you your own research.

Yes, there are exceptions. But the truth is: you are much more likely to understand and remember the information if you are exposed to a few of these styles when learning it. With this in mind, we have designed courses at Quanta in a certain way. It is intuitive, but here is an overview as well as a few suggestions for you:

1. Just like any course, it has a bunch of lessons. Each lesson (but the last one) has a "classwork", a set of theoretical and/or fun facts and also exercises; and a “Problem Set” which is self-explanatory;
2. You should start with a video (or sometimes text) at the top of the classwork. Even though it will overlap with parts of what is written below, please watch it anyway. Don't forget the comment from the above and that "Repetition is the mother of learning";
3. Each classwork has exercises, which come with solutions. Take your time thinking about them before revealing the explanation and even if you are sure you have solved them, still go through the explanations. They might have extra comments that are of paramount importance;

Should you have any questions or suggestions, feel free to email us at hello@quanta.world. Good luck!

Well, the name speaks for itself pretty well. But let's briefly overview each of the six lessons from this course anyway:

1. The first lesson is quick-overview of probability applications plus the first steps into the maths of probability.
2. The lessons 2 to 6 are each focused on a particular application or an important discussion related to probability theory. Thus, by the end of this course, not only you will know that probability is needed in, for example Machine Learning, or trading, you will actually see how it could be used. You will even get to solve problems for each of the topics.

But don’t worry, it is beginner friendly as promised: if you know what functions and x & y coordinates are, you are definitely good to go. Even if you know just that 1/2+1/3=5/6 you can understand like 60% of everything. Actually, the course is not mathsy overall. It has more discussions and observations rather than tough maths problems.

More sophisticated maths, theorems, problems, etc... are reserved for the following courses. So don't expect to build your first AI model, understand p-values and get an introduction into measure theory in this course. All that is planned for later.