24-Hour Non-Stop Profit Machine: The Ultimate Guide to Crypto Automated Trading with Vibe Coding

Creating a crypto auto-trading bot that makes a profit even in a bear market?!

"If you don't find a way to make money while you sleep, you will work until you die."

— Warren Buffett

Looking at this quote, one thought came to mind.

'What if I could build my own trading bot that generates profits in both directions within a market that fluctuates even while I sleep?' 🤔

That is how this course began.

Instead of a high-risk system that gives all authority to AI and leaves the entire investment to it,
we will implement the trading strategy designed in the lecture into an automated trading system through Vibe Coding to generate profits!!

An automated trading bot that has been in actual operation since the course opened (regular updates planned)

Ripple(XRPUSDT) Short 7x · +77.99%

Doge (DOGEUSDT) Long 5x · +28.81%

In an era where AI handles trading on its own, how can we automate more safely? 🤔

The answer lies in strategies verified through backtesting and Vibe Coding!

This course does not leave all investment decisions to LLMs like ChatGPT and Codex; instead, humans define the trading strategies and risk management criteria, while the LLM is utilized to assist with strategy design, code writing, and error resolution.

In this course, we will implement a Binance futures automated trading system using Python and CCXT. We will practice implementing technical indicator strategies, long/short/bidirectional strategies, martingale backtesting, Upbit API-based Kimchi Premium strategies, and furthermore, implementing trading strategies using LLMs, followed by building and deploying a trading bot.

After adding SNS API notification and order safety verification features, the completed bot will be managed via GitHub and deployed for free on an Ubuntu server in Oracle Cloud.

Aren't we relying too much on LLM..?

In the lecture, the LLM is used as follows.

Human Idea → LLM Strategy Design → Backtesting → Risk Validation → Automated Trading Execution

In other words, the LLM is used as a coding agent, and we are not handing over all our critical authority to the LLM!

Course Features

📌 You can start even if you have never coded before.

We will learn everything necessary for automated trading step-by-step, from installing Python to variables, conditional statements, loops, functions, and pandas. Understanding the basics of Python will allow for smoother communication with the LLM during Vibe Coding.

Furthermore, you can understand the logic process of automated trading by practicing with the CCXT library based on Python.

📌 Experience the process of Vibe Coding, not just copying code.

You will learn how to write strategy requirements and generate, modify, and debug code using ChatGPT and Codex.

📌 We cover everything from backtesting to real-world operation all at once.

You will personally handle everything from strategy design, performance analysis, and live ordering to API notifications via SNS, GitHub management, and cloud server deployment.

📌 LLM is not a trader, but our assistant.

We do not entrust funds to the improvised judgments of the LLM.

We implement the bot using a Human-in-the-Loop approach, where humans control the strategy and risk management standards!

In other words, Artificial Intelligence (AI) is utilized as a coding and strategy agent, but it is not used as an agent for executing trades!

Recommended for these types of people

After completing the course

• You can retrieve market price, balance, and order information using Python and CCXT.

• You can design your own trading ideas into specific entry and exit conditions.

• You can create new automated trading strategies and code using ChatGPT and Codex.

• You can analyze ROI / cumulative return / win rate / maximum drawdown / Sharpe Ratio / number of trades / fees.

• You can backtest long / short / bidirectional strategies and expand them into live trading code.

• You can implement features for order quantity validation, balance checks, duplicate order prevention, stop-loss, take-profit, and error handling.

• You can receive notifications regarding order executions and errors through the social media platform used in the course.

• You can manage your automated trading projects using Git and GitHub.

• You can run your auto-trading bot 24/7 on an Ubuntu server from Oracle Cloud.

Upon completing this course, you will have more than just simple example code;

You will have your own automated trading system that you can directly modify, test, and deploy!!

Here is what you will learn.

The person who created this course

• Graduated from a Computer Science and Engineering program at a top-tier university (Sogang/Sungkyunkwan/Hanyang level)

• Enrolled in the Graduate School of Engineering at Seoul National University

• Time series data analysis / Large Language Model research

• Performed outsourcing for automated trading program development for about half a year

• Stock / Crypto data analysis and automated trading algorithm development

Hello. I am Com-gong-ji-gi, currently researching time-series data analysis and large language models at Seoul National University's Graduate School of Engineering.

For about half a year, I have been working as a freelance developer for an outsourcing specialist, Company K, where I have turned clients' trading ideas into functional automated trading programs. In addition to my research on LLMs, I have been consistently analyzing data patterns in the stock and cryptocurrency markets and implementing various trading strategies through backtesting and automated trading algorithms.

I am also participating in the market by automating various trading strategies with the goal of achieving financial freedom. In this process, I have experienced numerous trials and errors, ranging from finding strategy ideas to Python, exchange APIs, backtesting, live trading, and server deployment.

Rather than explaining complex theories at length, this course aims to deliver the process of creating an actual coin automated trading program using Python and Vibe Coding in an easy and systematic way. It is structured with a focus on practice, starting from the basics so that even those new to programming can follow along step-by-step.

Through this course, I hope you gain the ability to not only execute the provided code but also to concretize your own trading ideas into strategies and directly test, modify, and deploy them.

Let's grow together and navigate the constantly changing market with your own system!

Do you have any questions?

Q. Can I take this course even if I don't know anything about coding?

Yes, it is possible. It includes everything from Python installation to basic syntax / pandas / and how to use development tools. By following the Python basics and problem-solving sections, you can proceed with the automated trading practice even without any prior coding experience.

Q. Is it okay if I have no experience with coins or futures trading?

Yes. We explain everything from the differences between spot and futures trading, long/short positions, and technical indicators to how to use Binance. However, since futures trading can lead to significant losses due to leverage, thorough learning and small-scale testing are necessary before real-world application.

Q. Is profit guaranteed if I create an automated trading bot?

No. This course is not an investment lecture that guarantees profits, but a technical lecture on backtesting strategies and implementing them into automated trading systems. Backtesting results do not guarantee future returns, and losses may occur depending on market conditions.

Q. Can I follow along on both Windows and macOS?

Yes. Although the lectures are filmed based on a Windows environment, Python / VS Code / Jupyter Notebook / Git / GitHub can also be used on macOS. There may be some differences in installation screens and commands depending on the operating system.

Q. Are ChatGPT Plus and Codex absolutely necessary?

For smooth Vibe Coding practice, we recommend using ChatGPT Plus and Codex. If you are using other LLMs or coding agents such as Claude or Gemini, you can apply the same strategy design and code generation processes.

Q. Can this be used on exchanges other than Binance?

The main practice sessions will be conducted using Binance Futures and Upbit-based Kimchi Premium strategies. Once you understand the common structure of CCXT and the Vibe Coding method, you can expand it to fit the APIs and ordering methods of other exchanges after the course.

Notes Before Taking the Course