[PY 0202] Python Level 2 for Artificial Intelligence

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

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.

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

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

This is a course that offers extensive practice in Python's basic syntax. This is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python's syntax.

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

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

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 a lecture on data visualization using the Matplotlib library.

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.

Learn virtual environment concepts and setup methods.

This is a course that offers extensive practice in Python's basic syntax. This is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python's syntax.

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.

You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.

QML is a programming interpreter language for creating UIs provided by Qt. It is similar to JSON and can use JavaScript. Using QML and Python together, you can easily develop modern, advanced UIs.

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.

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.

Prepare perfectly for the Programmers Coding Essential Competency Certification (PCCE), from Python basics to competency certification!

For those looking to learn Data Science, Big Data, and Crawling, (1) we will summarize the most essential Python core syntax in a short time, and (2) you will become familiar with Python and crawling through practical crawling programming.

This is a basic DFS lecture that explains the way a liberal arts major and working developer studied to get a job :) We have prepared a lecture where you can learn by solving problems yourself, with minimal boring theory lectures! After taking this lecture, you will be able to solve silver level DFS problems on your own according to Baekjoon standards.

A course where you can not only build programs required for blog operation using Python, but also earn additional revenue through sales and branding.

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

You will learn techniques that can be applied in various fields of IT security, starting from the introduction to Python programming.

Solve coding test problems using Python.

We will develop a web app that collects data using concurrent/parallel programming in Python, loads it into MongoDB, analyzes it, and visualizes the collected data using FastAPI, a modern web framework. In the process, you will learn and understand Python concurrent/parallel programming using coroutines, multi-threading, and multi-processing, and understand how to use them to improve Python's performance. We will help you apply Python concurrent/parallel codes directly to your work. We will not only teach you how to develop and end, but also how to deploy and operate an actual app on the AWS cloud.

A Complete End-to-End Developer Journey — Build Lightning-Fast APIs, Modern Frontend Interfaces, Real Projects, Authentication Systems, Dashboards & Full Deployments Using FastAPI, React, and Vibe Coding Techniques.

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. :)

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

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.

"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.