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

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.

[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 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.

[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 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.

A lecture consisting of special lectures by professors from Canadian national universities. It covers Python, Code, Scratch programming introduction/basics and practical applications. After completing the lecture, receive a global certificate from Codesprint : )

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.

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.

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 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. :)

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.

From the basics of Python to applications, everything you can do with Python, including web, data analysis, crawling, business automation, GUI, and programming, is covered in one course.

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.

This course provides a complete introduction to programming with Python. You will start from the very basics and gradually build up to writing more advanced scripts and solving real-world coding challenges. With step-by-step explanations, practical exercises, and projects, this course is perfect for anyone looking to start their coding journey or strengthen their foundation in Python.

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

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

AI does the coding, I get the results! Maximize practical programming skills, achievable even for beginners!

In this course, you will learn how to program kernels and develop PyTorch modules. You can use the knowledge you have gained to develop models faster.

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.

Learn NoSQL technology, which can handle Big Data, one of the fundamental technologies in full-stack and data science utilized by modern startups. MongoDB is the easiest and quickest technology to utilize among NoSQL databases. In this lecture, you will learn the basics of MongoDB in a short time, and also acquire the skills to manipulate and utilize MongoDB with 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.