[PY 0201] Python Level 1 for Artificial Intelligence

Limits of functions, derivatives, differentiation, derivative formula, applications of differentiation

This is the first lecture in linear algebra, and it is a lecture that geometrically understands vectors and vector operations.

This is a lecture on how to use NumPy and practice its application in real-world scenarios.

This is a lecture on data visualization using the Matplotlib library.

This is a lecture that condenses the math content learned in middle and high school. You will learn the necessary mathematical knowledge and techniques for each item with a lot of practice.

[Python for AI] This is the fourth lecture in the series. It is a lecture that covers Python grammar along with practical exercises used in machine learning and deep learning.

[Python for AI] Third lecture in the series. Learn how to debug Python code.

This is the second lecture in the [Python for AI] series. It's a lecture that provides practical exercises used in machine learning and deep learning, alongside Python grammar.

This course teaches you how to use LaTeX to write formulas.

Learn virtual environment concepts and setup methods.

This is a lecture on implementing practical code using PyTorch features based on the code directly implemented in Gradient-based Linear Regression (1). Additionally, it's a lecture where you'll theoretically learn about the necessity of data preprocessing, its theory, and its impact on learning, and implement it with practical code.

This is a lecture for perfectly understanding the process of training the simplest form of deep learning model using gradient descent.

This is a course that intensively covers gradient descent, the most fundamental learning algorithm in deep learning.

This is a course where you learn the basic calculus and PyTorch's Autograd functionality needed to get started with deep learning.

This is the fifth lecture in the [인공지능을 위한 파이썬] series. It is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python grammar.

[Python for AI] This is the fourth lecture in the series. It is a lecture that covers Python grammar along with practical exercises used in machine learning and deep learning.

This is the second lecture in the [Python for AI] series. It's a lecture that provides practical exercises used in machine learning and deep learning, alongside Python grammar.

This course covers everything from the basics to hands-on practice of AI platforms, and is a program where you can learn AI image generation technology. Learners can understand the fundamental concepts of AI and develop the ability to generate AI images using various tools and technologies. Through this course, you can enhance your understanding of the AI field and learn how to directly generate AI images in real-world applications.

A course to truly make you a hands-on game developer. Push your limits with 4 hands-on projects and 3 AI-specialized games!

Learn network programming from scratch, fully utilizing Python and ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly writing network code through practical exercises and personally verifying how their written programs operate. You can acquire skills ranging from basic network practicals to network technologies applicable in real-world scenarios, and build deep understanding and proficiency through exercises dealing with various protocols and tools. Furthermore, by leveraging ChatGPT, students can have a memorable learning experience without feeling difficulty or boredom.

This course is an AI music generation introductory program designed so that even learners who are new to artificial intelligence (AI) technology can easily understand and follow along. Through the lectures, you will learn the basic concepts and usage methods of AI platforms, and proceed step-by-step through hands-on practice to create your own music using these tools. Going beyond simply pressing buttons to make music, this course guides you to understand the principles of AI models and the key factors that influence music generation, and to complete creative results by adjusting the desired atmosphere, genre, and instrumental composition. Upon completing the course, you will gain confidence in using AI in a friendly manner, along with AI music generation capabilities that can be applied to various fields such as daily life, projects, and content creation.

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.

You can easily and enjoyably understand Python programming with games. This is a lecture that even children in elementary and middle school can follow, so parents and teachers will find many places to use it if they learn it. :)

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

From the basics of Numpy and Pandas to data preprocessing, visualization, and crawling, all in one place! This is an introductory Python course for data analysis.

Django Base Camp is a course where you can systematically learn the core of the Django web framework from beginner to intermediate level. You can quickly develop the ability to build web applications through project-oriented, practical classes.

From Python fundamentals to practical data analysis! You will learn practical Python skills for processing, visualizing, and analyzing data while solving business problems.

This course is a hands-on program that covers everything from the basics of understanding and utilizing AI platforms to AI image generation technology. Learners can master the fundamental concepts and tools of AI and develop the ability to generate AI images using these skills. The course is designed to be easily accessible even for learners who are new to AI technology, providing an opportunity to quickly master AI image generation techniques that can be applied in real life.

During our school days, the 'click' sound we heard in the computer lab... that was Minesweeper. In this course, we'll recreate those memories by implementing it with Python. Whether you're a beginner or even someone encountering Python for the first time, by following along line by line, you'll find that your very own Minesweeper game has been completed before you know it.

Let's find out how to automate tasks using Python!

This is a lecture for people who are starting development for the first time. It's about programming thinking, which should come before development languages or UI frameworks.

Data analysis sounds a bit grandiose, but it is actually a process of establishing a hypothesis and verifying it based on data. You can learn how to analyze what data to verify your hypothesis using Python.

Theory, numerical approximations, intuition, and visualization in integral calculus. Enhance your math-coding skills.

"Automating your work? Who doesn't know what's good for them?" You don't need to use a knife to catch a chicken. I want to show you that 10 lines of simple code are more practical than complex crawlers on the Internet.

Coding Test [ALL IN ONE] ✔️ Complete with one lecture