Fundamentals of Statistics and Data Analysis

We will introduce the types of big data analysis techniques and Python libraries for analysis, and the basics of statistical analysis techniques and machine learning analysis techniques.

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.

Statistics learned in school, was it too hard to understand? No matter how much you listened to the explanation, statistics were confusing, but we will help you understand them. If you implement them one by one by hand using Excel, you will understand statistical concepts that you didn't understand! A new experience that makes boring statistics fun! We will give you a gift. :)

Let's build a solid foundation in Python and solve data analysis problems!

Let's collect and refine data through public data, web scraping, and more, and perform exploratory data analysis!

If you're wondering, "I did the user research... but is this result truly representative of all users?" then pay attention! We will show you exactly how to add persuasiveness to your designs based on data. ✅ We explain complex statistical terms in very simple language. ✅ We carefully introduce the 3 core hypothesis tests essential for UX practice, covering everything from principles to hands-on practice. ✅ We show you how to easily analyze user data using AI—without costs or hallucinations.

A course to understand and practice machine learning for efficiently conducting complex analysis and predictions! Even machine learning, which may seem difficult and complex, can be easy and fun to master with Masocampus's <Python Machine Learning>.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

Let's cultivate professional expertise in programming, algorithms, and statistical analysis!

Feeling overwhelmed by where to start with complex data analysis? I will clearly guide you through how to utilize R and AI Tutors using the practical know-how I've built up.

This course aims to acquire Python-based web crawling technology to collect data from web pages and improve data collection and analysis capabilities at work based on this.

Build data-driven investment strategies with Python quant investing and put them into practice. You can implement various asset allocation strategies and ultimately create your own unique investment strategy.

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

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

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

An introductory course that teaches the core principles of AI—from Python and data analysis to machine learning, text mining, deep learning, and Transformers—with a focus on theory and hands-on practice of key topics.

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

Revolutionize your stock investing with AI! In this course, you’ll build a fully functional AI automated trading system that targets the top 25 Nasdaq stocks. Gain experience and know-how through paper trading with the Korea Investment & Securities API, and take advantage of this special opportunity to conduct AI-powered automated stock trading with a real account. Even if you’re a complete beginner, there’s no problem. We’ll explain the basic concepts of stocks and why you should invest in U.S. stocks in an easy-to-understand way, and provide all source code along with remote support. From now on, investing is essential for the next 60 years of our lives. Build your own AI investment partner to accompany you!

Those who have learned the basics of Python will learn how to utilize Python after watching this lecture.

"Why does my automated trading system collapse in a declining market?" I, too, have wrestled deeply with the same question. Most automated trading logic on the market may appear to generate profits during bull markets, but the moment market conditions change, it loses its ability to adapt. To solve this problem, I combined the expertise I developed through two years of hands-on research with the latest AI technology. In this course, you will learn how to design a 'Transformer-based deep learning model' that simultaneously reads macroeconomic trends and the movements of individual stocks, and how to automatically train and deploy it in a free GPU environment. In particular, by introducing sophisticated, hedge-fund-level data normalization techniques, you will build an 'intelligent comprehensive scoring system' that goes beyond simple indicators by incorporating short-selling balance and order-flow data. On top of that, an ‘AI safety gate’ infused with the insight of a Wall Street trader with 20 years of experience provides the final confirmation from the perspective of a human trader just before a purchase. Going beyond simply buying and selling, you will implement the entire process of an institution-grade algorithmic system with dynamic take-profit and stop-loss logic, eight self-recovery mechanisms, and real-time Slack reporting—all with your own hands.