AI for everyone: the first step to deep learning understood by mathematics

A class that goes beyond “using” AI and “understands” it

ChatGPT, recommendation systems, and even autonomous driving. AI is already deeply embedded in our everyday lives.

However, even though many people know how to use AI I have a vague feeling why it works the way it does.

This class explains the core concepts required to properly understand AI by connecting them step by step from the beginning.

Overseas courses are burdensome in English, and domestic AI introductory courses often focus only on coding exercises. On the other hand, this class Functions, exponentials/logs, calculus, probabilityFrom the basics of mathematics such as vectors and matrices, artificial neural networks, backpropagation, softmaxIt has been designed so that the core principles of AI can be understood in a single flow.

It's not just a course about memorizing formulas or writing by following code.

How functions define AI inputs and outputs
How differentiation determines the direction of learning
How backpropagation transfers errors and trains models

It is explained so that it can be easily understood through formulas, intuitive pictures, and various examples.

Experience gained by developing actual models at AI contests and AI learning platforms AI for everyoneBased on a curriculum verified by thousands of learners while operating, we have carefully selected only the most difficult concepts in the field.

After all, a good AI model starts with a solid foundation.

No coding experience is required.

It's okay if you learned math a long time ago.

If you have a desire to properly understand AI, we will work with you so that everyone can follow along until the end.

I recommend it to people like this

Those who use ChatGPT and generative AI but want to properly understand the principles of AI
Those who have taken AI courses that focus on coding but feel that mathematical concepts are lacking
University students, job-seekers, and office workers who want to learn machine learning and deep learning in a systematic manner
Those preparing for a career transition to AI-related jobs (development, data, planning)
Teachers and lecturers who want to have a solid foundation to teach AI to students
Those who are burdened with English lessons and want to learn AI from the basics in Korean

What you learn in this class

1. The language of mathematics for AI

Understand how functions, exponents, logs, calculus, probability distributions, and trigonometric functions are used in real AI.

2. Understanding the structure of deep learning

Learn from vectors and matrices to linear layers, activation functions, artificial neurons, hidden layers, and deep neural networks in one flow.

3. Understanding how AI learns

We understand the process of AI learning on its own through slope, slope descent, chain law, backpropagation, and softmax.

4. Develop thinking skills that lead to practice

When model performance is not as good as expected, we have the foundation to analyze the cause and think about the direction of improvement on our own.

Understanding the world of basic deep learning through basic mathematical principles

Understanding the world of basic deep learning through basic mathematical principles