Python Algorithmic Trading Part 2: Real-Time Algorithmic Trading with the Interactive Brokers API

Packed with LLM Fine-Tuning Know-how, learned from Silicon Valley LLM Project Practitioners.

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

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

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.

This lecture is a follow-up lecture to 'Python Data-Based Stock Quant Investment Part 1'. If Part 1 was more of an introduction, Part 2 is an in-depth lecture that focuses on the entire flow of practical strategy implementation and quantitative investment development. This class focuses on advanced Pandas techniques for handling time series data, and how to implement signal-based strategies and static/dynamic asset allocation strategies that require adjusting asset weights at various intervals based on this. Furthermore, it goes beyond strategy implementation and learns about 'code framework' that directly verifies and backtests various investment strategies with minimal code modifications, how to extend this to improve it so that it can lead to actual investment, and what to watch out for in this process. In addition to the programming component, you can experience the best Python quant investment flow that you cannot find in investment books, blogs, YouTube, etc. by deeply covering theoretical contents such as the two types of return concepts (simple return, log return) and evaluation indicators related to backtesting.

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

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

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.

Prepare perfectly for the Programmers Coding Essential Competency Certification (PCCE), from Python basics to competency certification!

QML is a programming interpreter language for creating UIs provided by Qt. It is similar to JSON and can use JavaScript. Using QML and Python together, you can easily develop modern, advanced UIs.

Do you want to create a tool that can help you with your real-world investments using Python? In this course, you will learn how to create an interactive web dashboard for financial data analysis for intermediate Python users and learn about pair trading strategies for in-depth quantitative work. We hope that you will be able to create your own useful analysis tools to help you analyze financial data more powerfully and make wise investment decisions.

This lecture is for beginners who are new to coding, as well as those who want to try out various uses of Python, covering basic concepts of Python, Numpy, Pandas, Plotly, Django, and crawling, as well as simple data analysis.

AI does the coding, I get the results! Maximize practical programming skills, achievable even for beginners!

I am not a major and currently working as a developer. I also learned a lot from Infraon, so I organized it mainly based on the concepts that I had difficulty grasping at first. I hope it will be helpful to someone. Thank you.

Analyze over 40 types of economic indicators and stock data with AI to create your own powerful stock price analysis model that predicts not only S&P 500 and QQQ ETF, but also individual stocks!

Learn how to use various libraries and acquire the theory and knowledge necessary to create related applications through Python, the easiest programming language to learn and the most widely used in a variety of fields.

Solve coding test problems using Python.

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

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

You will learn techniques that can be applied in various fields of IT security, starting from the introduction to Python programming.

Strengthen your coding skills through coding test problems by learning Python-based data structures and algorithms!

You can easily and enjoyably understand Python programming with games. This is a lecture that even children in elementary and middle school can follow, so parents and teachers will find many places to use it if they learn it. :)

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

This is a Unity C# scripting course for absolute beginners who are learning programming for the first time. It was created by carefully selecting the core grammar necessary for utilizing Unity scripts.