[PY 0205] Python Level 4 for Artificial Intelligence - Objects and Classes

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

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

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.

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 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 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.

Learn Python easily and quickly with patterns. Learn only the essentials in a concise manner 💪

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.

You will thoroughly understand the principles!

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

"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.

If you are planning a service, a website is an essential element. Of course, in addition to the service, most of the currently provided program infrastructures operate based on the web. The purpose of this course is to learn how to create a website using Python, which is considered the easiest programming language, and how to set it up to an actual operational state.

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

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.

In this course, you will learn the basics of Raspberry Pi and Python and practice creating simple but essential self-driving car and remote home monitoring projects.

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.

Learn how to use various libraries and acquire the theory and knowledge necessary to create related applications through Python, the easiest programming language to learn and the most widely used in a variety of fields.

It would be efficient to automate IT security tasks using Python, wouldn't it? This course follows hands-on practice, applying Python and web Flask development to automate tasks, idea by idea.

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

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.

This course covers the process of automating algorithmic trading in local and cloud environments, and focuses on hands-on practice.

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

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.

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.

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