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

Build a solid theoretical foundation of images essential before learning deep learning-based computer vision. Understand the essence of image data, such as pixels, resolution, and color representation, and cultivate practical programming skills to read, transform, and preprocess images using Python.

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

This is a lecture that condenses the mathematics curriculum taught in middle and high school. You will learn the necessary mathematical knowledge and techniques through extensive practice for each item.

This is a lecture that provides a brief introduction to the field of computer vision.

We will summarize the theoretical concepts of MNIST, the most fundamental dataset in computer vision, and learn how to implement it using Torchvision's API as well as how to implement a custom dataset class directly.

This course provides a complete theoretical overview of the operations of convolutional and pooling layers, which are the core modules of Convolutional Neural Networks, and helps you develop implementation skills by building them yourself.

This lecture focuses on convolution, the most important operation in computer vision using deep learning.

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 a lecture on data visualization using the Matplotlib library.

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

[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 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.

Limits of functions, derivatives, differentiation rules, derivative formulas, applications of differentiation

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

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 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.

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

You will thoroughly understand the principles!

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

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

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.

A course where you can create programs for running a blog using Python and generate additional income through sales and branding.

If you are planning a service, a website is an essential element. Of course, beyond services, most current 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 one of the easiest programming languages, and to set it up for actual operation.

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

Do you manually type in numerous commands every time you build a complex project or create a deployment package? Currently, most open-source projects use build automation scripts to save the trouble of typing commands. Do you also find building tedious? Then use this course to automate your builds and increase your work efficiency.

1. A practice-oriented lecture designed to help you pass the AICE Associate, Korea's only nationally recognized AI certification. 2. Learn to the level of performing data analysis and AI modeling based on Python.

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.

I recommend this to those who want to possess their own technical skills and those who want to learn web development step-by-step. We teach everything starting from the history of web browsers and languages.

Django Base Camp is a course where beginners to intermediate learners can systematically master the core of the Django web framework. Through project-oriented practical lessons, you can quickly develop the ability to build web applications.

This is an advanced course where you will directly implement and interpret practical statistical techniques such as sampling distributions, hypothesis testing, regression analysis, and logistic regression using R. By utilizing AI tutors like ChatGPT and Gemini, you will learn everything from code generation to interpreting analysis results and writing reports, allowing you to take your data analysis capabilities to the next level.

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.

Learn about the basics of Python required for data analysis, the data analysis framework (pandas), and the data analysis process.

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.

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