Phương pháp đầu tư dựa trên dữ liệu trọn đời với đầu tư định lượng Python

This is a full-stack restaurant map tutorial that allows you to learn everything from front-end, back-end, Kakao Map API usage, and deployment all at once while creating a restaurant map of your favorite YouTuber.

This is a lecture where you can learn Deep Learning using TensorFlow. Learn linear regression, logistic regression, and softmax regression models, and finally create an MLP model that can classify fashion images!

This course will help you quickly learn the core concepts of Python and the Pandas library. Improve your programming skills by solving the practice problems at the end of each part!

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.

In this class, you will learn about the principles and methods of analyzing and processing various types of financial data using Python's Pandas library, apply them to situations you may encounter in the real world, and ultimately learn how to implement backtesting based on financial statement data (based on Kang Hwan-guk's book, "You Can Do Quant Investment"). As a result, you can break away from being a "passive investor" who simply follows what others say without verifying or basing the investment logic, and become a "self-directed and active investor" who can freely extract various elements necessary for strategy implementation from data and quantitatively analyze them using Python and Pandas.

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!

Leverage Python to create your own indicators and a convenient tool for securities analysis!

When you use Pandas for data analysis, preprocessing, machine learning, and deep learning, you tend to use only the functions you use frequently. There is a Pandas Cheat Sheet that collects and organizes only these essential contents. For those who get tired of learning Pandas from a thick book, we will teach you Python Pandas with just two pages of documents. Learn the core functions of Pandas with the cheat sheet provided in the official Pandas tutorial.

The fact that you can analyze data more easily and effectively with Python Pandas instead of Excel! Learn the basic functions of the Pandas library and how to use it in practice through financial data analysis.

This is a basic course on Python Excel programming that you can learn with the xlsxwriter tutorial. You can analyze data and automate tasks using Python and Excel.

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.

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.

Automated trading program, source code ready-to-use! Deploy to production with Oracle Free Tier server!

🚀 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.

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.

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.

A course to understand and practice machine learning that efficiently performs complex analysis and prediction! Machine learning, which seemed difficult and complicated, can be easily and enjoyably learned in its core with Maso Campus' <Python Machine Learning>.

Now display Python results as web pages! You can create your own web page using only Python. This is an opportunity to create an Interactive Dashboard that allows you to check results created with Python, such as data analysis and machine learning, on a web page!

Finally, a probability and statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice.

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

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

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

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.