[PL 0303] Python for Data Visualization - Matplotlib Master Class

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 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 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.

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

Create your own real estate analysis system with Python and learn the most effective methods for data preprocessing and visualization.

Leveraging Python's basic syntax and popular libraries Auto-generating Python syntax and library code using ChatGPT

The Intermediate Python course is designed to deepen your understanding of Python by covering advanced topics such as functional programming, metaprogramming, exception handling, and object-oriented programming.

This course aims to acquire Python-based web crawling technology to collect data from web pages and improve data collection and analysis capabilities at work based on this.

Analyzing customers, markets, and revenue patterns—you no longer need to learn it yourself. Just ask AI, and expert-level analysis and strategies are completed in an instant!

In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.

Those who have learned the basics of Python will learn how to utilize Python after watching this lecture.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.

We guide non-majors and beginners to quickly obtain the Big Data Analytics Engineer practical certification! Theory lightly, practice thoroughly - even without complex background knowledge, we focus on learning only the essential points that appear on the exam, centered around past exam questions.

It's now an era where data speaks, not intuition. Learn data analysis easily with ChatGPT!

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

AI that thinks and adapts? Now you can build it yourself. Master the core of reinforcement learning with intuitive explanations and code, not complex theories, and grow into a 'practical developer' through finance and industry projects.

Let's develop specialized skills in programming skills, algorithm skills, and statistical analysis skills!

Now display Python results as web pages! You can create your own web page using only Python. This is an opportunity to create an Interactive Dashboard that allows you to check results created with Python, such as data analysis and machine learning, on a web page!

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

You can learn the skills and know-how needed to improve work efficiency by utilizing Open API and Python.

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

Revolutionize your stock investments with AI! In this lecture, you will directly build a real, working AI automated trading system targeting the top 25 NASDAQ stocks. We provide a special opportunity to gain experience and know-how through simulated investments with the 한국투자증권 API, and to perform AI stock automated trading with a real account. Even stock beginners will have no problem. We will easily explain basic stock concepts and why you should invest in US stocks, and provide all source code and remote support. From now on, investment is essential for the next 60 years of our lives. Create your own AI investment partner that will be with you!

🧩 Rather than focusing on complex formulas or theory-centric explanations, the goal is to learn the core concepts of recommendation systems by directly implementing programs. 🛠️ Through a total of 12 diverse and practical examples, we have progressively designed recommendation systems that can be utilized in real-world environments, including content-based recommendation, collaborative filtering, and deep learning recommendation.