LLM Finetuning : RunPod and Multi-GPU Practice
danielyouk
Packed with LLM Fine-Tuning Know-how, learned from Silicon Valley LLM Project Practitioners.
Basic
LLM, RunPod, openAI API
You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.


Reviews from Early Learners
5.0
Hoon
It's a really special lecture at Infraon. You can adapt to any part, and if you follow the instructor's explanation, you'll feel like, "Ah, this is it."
5.0
법경
Very good
5.0
Jc
Thank you for explaining it step by step.
Implementing an automated trading system with Python connected to the Interactive Brokers API.
Data-driven Trading and Investment
In-depth Understanding of Python Object-Oriented Programming (OOP)
Real-time trading and trade schedule management
This course is designed to educate algorithmic trading and coding automation from a developer's perspective . The course content focuses on developing investment strategies and simulating them , and does not cover account opening, legal procedures, tax-related matters related to actual investments, etc. In addition, it does not serve as investment advice or financial counseling , and matters related to actual financial transactions should be carried out at one's own risk.
All trading strategies covered in the course are based on simulations and are for educational purposes only. If students have questions related to investing or trading, please understand that we cannot answer questions that are outside the scope of the course.
Part 2 is required to take Part 3 , and Part 1 is recommended.
Part 1 - 'Python Data Analysis for Algorithmic Trading'
Part 2 - 'Real-time algorithmic trading using Interactive Brokers API' (main lecture)
Part 3 - 'Cloud Transaction Automation'
Learn how to automatically launch virtual machines to match your stock trading schedule with cloud automation.
There is a course review event. Please leave a course review for Part 1 and contact us by email (daniel@datatrain.education ) and we will issue a voucher for an additional 20% discount from the current price .
Please refer to the last public lecture of Part 1 lecture.
Why is API connection important in quant lectures? 🤔
I want to invest in US stocks, but is there an efficient way ? 🧐
What if my strategy loses money in automated trading ? ❓
How do I apply my own strategy based on proven strategies ? ❓
•••
This course was created after much thought on whether it would be possible to include a universally applicable 'method' in the course so that any investment strategy can be put into practice immediately. The use of the API of Interactive Brokers (IBKR), the world's No. 1 market share, will enhance your investment execution ability.
Interactive Brokers (IBKR) offers a variety of tools to help clients manage their assets effectively in over 150 markets worldwide. IBKR stands out as an online brokerage service thanks to its low transaction costs and advanced trading technology, and has been ranked #1 in Barron's annual Best Online Brokers review for six consecutive years.

✅ Simple registration process : (For simulation purposes) You can register with just your email address.
✅ Super-simple API connection : Connecting the API to Python is as simple as two clicks.
✅ Practice is the answer : Any investment strategy can be simulated in real time through actual trading.
✅ Initialization Settings : You can initialize the funds in your paper trading account, making it easier to test new strategies.
✅ The answer is global : You can access global financial markets, including US stocks, through the IBKR API.
Despite the above advantages, the reality is that there are few lectures that apply the IBKR API, which has the world's No. 1 market share in Korea. This lecture connects the IBKR API to Python to create a pipeline that can trade in real time.
✅ Optimized trading with daily updates
Every morning, we select the optimal stock pairs and trading parameters based on the latest market data. This allows us to quickly respond to changing market conditions, maximizing the efficiency of your investments.
✅ Automated trading execution with Python and IBKR API
The updated portfolio is imported directly into a Python script, and trades are automatically executed via the IBKR API within minutes. The whole process is easy and fast.
✅ Ensures stability by preventing duplicate transactions
If there is a delay in the trading signal, the script automatically checks the signal transmission time to prevent duplicate transmission. This reduces unnecessary trading risks and maintains stable trading.
(Left: Python script vs. Right: Real-time trading via Interactive Brokers API)
'Inheritance', one of the core principles of object-oriented programming, allows you to create a completely new class by extending or modifying the functionality of an existing class. In this process, the inherited class can shorten development time and maintain code consistency by reusing the properties and methods of the base class.
Blocking and organizing your code is an often overlooked part of programming. When it comes to efficiently integrating external code and building on it to add new features, well-structured code offers the following benefits:
Performance Improvement : By reusing existing components, you can improve the performance of your overall system.
Ease of debugging : When the structure of your code is clear, it becomes easier to find and fix errors.
Extensibility : Code with a well-defined structure makes it easy to add new features or modify existing ones.
In our lectures Let's take the 'PairsTradingUpdatePosition' class as an example and see how this class can be extended by inheriting from other trading strategy classes through real code. Through this process, you will learn specifically how inheritance is applied to real code and how it affects code maintenance and optimization.

Access global markets through Interactive Brokers API, the world's #1 market share
Automatic algorithm updates and execution reflecting the dynamic characteristics of the market
Access to real-time data via Yahoo Finance, not historical data
Everything is an object. Deep object-oriented programming
This lecture is the second lecture of [Python Algorithm Trading].
Part 1: Python Data Analysis for Algorithmic Trading
Part 2: Real-time algorithmic trading using IBKR’s API
Part 3: Cloud Automation (September release)
All Python scripts are attached to the lecture materials.
Q. Do I have to take Daniel Instructor’s Quant Part 1 lecture?
No, the purpose of this course is to put investment strategies into practice.
Since this course requires an investment strategy, there is a Part 1 lecture on the process of creating an investment strategy.
Q. How much Python knowledge is required?
This lecture is aimed at intermediate Python students. The lecture proceeds by guiding the installation process of Visual Studio Code or Conda without directly covering it.
Additionally, the lecture assumed a basic understanding of Python's object orientation.
Q. So, beginners can't take the course?
Based on my experience conducting in-house Python training at my company, I can say that the training results were the best when we trained while producing actual results.
Even if the lecture is difficult, I recommend it to beginners who can challenge themselves by looking up related materials and asking questions to the knowledge sharer.
Q. What about time difference issues when executing automated trading targeting US stocks?
When taking the course, we recommend that you study the last lecture (Section 4: Completing Real-Time Trading) during the US stock market opening hours (after 10:30 PM).
In the upcoming Quant lecture [Part 3], we aim to automate all processes in the cloud to achieve automatic trading without time lag issues.
Who is this course right for?
Looking for individuals who have taken the "Python Algorithm Trading Part 1" course or have an understanding of object-oriented programming.
For those looking to automate stock trading
Traders and investors looking to upgrade their trading activities to a professional and automated system
Need to know before starting?
Python Object-Oriented Programming
673
Learners
73
Reviews
74
Answers
4.8
Rating
7
Courses
Working as a Pod Lead at an LLM-based AI company
Seoul National University Graduated from the Department of Mechanical and Aerospace Engineering
Master's degree in Mechanical and Aerospace Engineering from a graduate school in Europe
Conducting doctoral research at an engineering research institute in Germany
Senior Data Scientist experience at a major European energy company
Active as a Senior Consultant at a UK-based energy consulting firm
Performed Databricks-based data engineering projects
Achieved Top 3% in Kaggle Stock Trading AI Competition
Currently serving as the AI Agent Development Team Lead
All
20 lectures ∙ (2hr 7min)
Course Materials:
All
19 reviews
4.7
19 reviews
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Average Rating 5.0
5
It was a short lecture, but it was condensed to the core, so I was able to watch it with focus. I was able to study the parts that I needed to understand more by repeating them or searching them, so it wasn't boring. I also felt like I could apply the lecture content to other places, so it was very helpful.
Thank you for leaving a review after completing the course. See you in the next lecture.
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Average Rating 5.0
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Average Rating 5.0
5
Thank you for the 1:1 session in this lecture!
I'm glad you found this helpful. Feel free to ask questions anytime you need anything.
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Average Rating 5.0
5
It's a really special lecture at Infraon. You can adapt to any part, and if you follow the instructor's explanation, you'll feel like, "Ah, this is it."
Hoon! Thank you for your meaningful review.
Reviews 51
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Average Rating 4.9
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