[PY 0203] Debugging Fundamentals

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.

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 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.

Python Programming Basic Hands-on Lecture taught by a professional Data Scientist! In this lecture, chosen by over 5,000 cumulative students, you can master Python from basics to practical application, step by step, with Selena. Living in the era of generative AI and LLM, the essential language you must learn is Python. This is a verified lecture that received 5 out of 5 stars based on high student satisfaction, and an unlimited Q&A open chat room is also provided where you can ask questions and communicate anytime while taking the course.

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.

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

"Most similar to real practice! Capture employment, coding competitions, and skills all at once." Perfect preparation for corporate coding tests! Skill improvement from basics to intermediate level! This course contains only the essentials needed for coding test preparation. Structured step-by-step from basic concepts to practical problems, you can simultaneously develop programming skills and practical sense.

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 : )

"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.

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.

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.

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.

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

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

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

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.

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.

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 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.

You will thoroughly understand the principles!

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.