Right now, Polars

Why does JavaScript use Classes? How was object-oriented programming implemented before their advent? Let's take a brief journey to find answers to questions you might ponder while studying JavaScript.

The secret to building websites usable by anyone without discomfort, through WCAG 2.2 guidelines and practical application know-how, create highly accessible services!

Learn to create and use practical Notion templates for daily life, including household ledgers, pet care, and collaborative year-end reflections. Beyond just attractive templates, this covers design for efficient data management and practicality, allowing deeper Notion usage.

A course for creating quality websites using just Notion and Oopy, without a developer or coding.

Develop your ability to find the core of a problem and solve it with the 'Top 10 JavaScript Algorithms' that cover the most frequently asked types of problems!

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.

🚀 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.

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.

When using Pandas for data analysis, preprocessing, machine learning, and deep learning, we often find ourselves relying on the same core functions. There is a Pandas Cheat Sheet that compiles only these essential features. For those who have grown tired of trying to learn Pandas through thick books, this two-page document will teach you Python Pandas. Master the core functions of Pandas using the cheat sheet provided by the official Pandas tutorial.

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

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

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!

This course focuses on developing practical visualization skills that can be immediately applied in the workplace by utilizing Seaborn, a core tool for data visualization, and plotly/Dash for building interactive dashboards. Through various hands-on exercises, you can enhance both your ability to create insight-driven visual materials and implement web-based dashboards.

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.

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

You can use Python to analyze large amounts of data and visualize the analyzed data in graph form so that you can easily understand it at a glance.

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

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.

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

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.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

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.

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

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

With Python Quant Investment, you can create investment strategies based on data and invest according to the strategy. You can implement various asset allocation strategies and ultimately create your own investment strategy.