Python Algorithmic Trading Part 3: Cloud Trading Automation

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

You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.

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.

You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.

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.

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!

A course where you can create programs for running a blog using Python and generate additional income through sales and branding.

This course teaches the process of [idea generation - data collection - verification through backtesting] for developing a Bitcoin cryptocurrency coin bot that can generate automatic profits, as well as the principles of the AIS1, AIS2 investment strategy developed by the instructor, stock selection and buying and selling points and backtesting, and the source code for bot execution.

The "Easy to Learn Intermediate Python" course provides a variety of examples and exercises needed to learn intermediate-level Python skills and solve real-life problems. You can easily learn advanced content such as object-oriented programming, module utilization, and data processing step by step.

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.

You will learn how to configure CI based on GitHub Actions and what content should be included in CI, and you can learn about verification through the SLSA Framework, which was a topic of discussion in Google DevOps Report 2022.

This is a course to learn large-scale traffic processing and real-time streaming through practical projects by integrating RabbitMQ, Kafka, and Redis with Python Flask.

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!

I have created an introductory CI/CD course that is easy to understand even for non-majors and can be applied immediately in practice!

In this lesson, we will create a program that creates a logic that can generate profits, buys and sells Bitcoin through an exchange according to that logic, and receives the results of the transaction via Telegram.

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.

It would be efficient to automate IT security tasks using Python, wouldn't it? This course follows hands-on practice, applying Python and web Flask development to automate tasks, idea by idea.

Have you studied Python syntax but felt lost when it came to actually handling data? You know you need to learn NumPy and Pandas, but if you've been wondering where to start and how to connect them, this PART 2 is the answer. In PART 2 of our 50-lecture data analysis curriculum, you will experience the step-by-step process of loading, cleaning, processing, and statistically interpreting real data. You won't just learn libraries and syntax; you will establish criteria for which tools to choose in specific situations. PART 2 is the turning point where you move from simply knowing Python code to actually being able to handle data.

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.

Let's learn how to translate real-life and major problems into actual computer programs and practice using Python-based artificial intelligence tools!

You will learn Apache Airflow, the most widely used Orchestrator for creating software data pipelines.

You will thoroughly understand the principles!

Learn network programming from scratch, fully utilizing Python and ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly writing network code through practical exercises and personally verifying how their written programs operate. You can acquire skills ranging from basic network practicals to network technologies applicable in real-world scenarios, and build deep understanding and proficiency through exercises dealing with various protocols and tools. Furthermore, by leveraging ChatGPT, students can have a memorable learning experience without feeling difficulty or boredom.