[PY 0203] Debugging Fundamentals

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

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.

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.

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

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 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 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.

A basic Python programming practice course taught by a working data scientist! Chosen by over 5,000 cumulative students, this course allows you to master Python from the basics to hands-on practice step-by-step with Selena. In the era of Generative AI and LLMs, Python is the essential language you must learn. This is a proven course with a 5-star rating based on high student satisfaction, and an unlimited Q&A open chat room is provided for you to ask questions and communicate at any time.

[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.

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.

This is a course where you can learn UML and object-oriented design even without programming experience. Concepts are explained through everyday examples (cafes, libraries, shopping malls), and you'll learn 9 types of UML diagrams step by step. You'll develop design skills that can be immediately applied in practice using theory and PlantUML.

For those who want to learn data science, big data, and web crawling, (1) we summarize the most essential Python syntax in a short time, and (2) you'll 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.

You will thoroughly understand the principles!

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

Feeling overwhelmed by where to start with complex data analysis? I will clearly guide you through how to utilize R and AI Tutors using the practical know-how I've built up.

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.

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.

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.

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.

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 : )

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

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.

Anyone can easily create a Python game using the Pygame library, starting from zero base.

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.

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.

Baekjoon Bronze 3 Level Core Problem-Based Coding Test Fundamentals Training