Pillow Investment Method: An AI Stock Auto-Trading Machine That Makes Money While You Sleep

"Why does my automated trading collapse in a bear market?" I have also deeply pondered this same question. Most automated trading logics on the market seem to generate profits during a bull market, but they lose their ability to respond the moment the market sentiment changes. To solve this problem, I have combined the know-how I researched myself over the past two years with the latest AI technology. In this course, you will learn how to directly design a 'Transformer-based deep learning model' that simultaneously reads macroeconomic trends and individual stock flows, and how to automatically train and deploy it in a free GPU environment. In particular, we will introduce sophisticated data normalization techniques at the hedge fund level to build an 'Intelligent Comprehensive Scoring System' that goes beyond simple indicators to incorporate news sentiment. To this, we add an 'AI Safety Gate' that implants the insight of a trader with 20 years of experience on Wall Street, adding a final layer of confidence from a human trader's perspective right before a purchase. Beyond simple buying and selling functions, you will directly implement the entire process of an institutional-grade algorithmic system by adding dynamic take-profit and stop-loss logic, eight self-recovery mechanisms, and real-time Slack reports.

Build your own powerful stock price analysis model that analyzes over 40 types of economic indicators and stock price data using AI to predict not only the S&P 500 and QQQ ETFs but also individual stocks!

By simply entering a US company ticker, this system automatically collects financial accounting data, competitor analysis, recent news, and stock price information to generate professional investment reports through in-depth analysis using the OpenAI GPT API. The final results are automatically uploaded to Notion. By learning the basic concepts and terminology of financial accounting, even engineers can utilize this for competitor benchmarking, persuading supervisors, and planning new solutions. You will build a high-performance API server using Python and FastAPI, learning asynchronous programming, AI integration, and practical fintech skills. We support beginners so they can easily follow along, complete a system applicable to real-world investment and business, and grow into developers tailored for the AI era.

An era where even IT beginners can become the 'CEO of their own platform' with just an idea, utilizing AI and Gnuboard! We will demonstrate the actual development process in detail, from planning to deployment, and even share various monetization methods such as advertising and shopping malls. Start your online business right now!

"Why does my automated trading collapse in a bear market?" I have also deeply pondered this same question. Most automated trading logics on the market seem to generate profits during a bull market, but they lose their ability to respond the moment the market sentiment changes. To solve this problem, I have combined the know-how I researched myself over the past two years with the latest AI technology. In this course, you will learn how to directly design a 'Transformer-based deep learning model' that simultaneously reads macroeconomic trends and individual stock flows, and how to automatically train and deploy it in a free GPU environment. In particular, we will introduce sophisticated data normalization techniques at the hedge fund level to build an 'Intelligent Comprehensive Scoring System' that goes beyond simple indicators to incorporate news sentiment. To this, we add an 'AI Safety Gate' that implants the insight of a trader with 20 years of experience on Wall Street, adding a final layer of confidence from a human trader's perspective right before a purchase. Beyond simple buying and selling functions, you will directly implement the entire process of an institutional-grade algorithmic system by adding dynamic take-profit and stop-loss logic, eight self-recovery mechanisms, and real-time Slack reports.

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

This is a course on building your own stock and cryptocurrency automated trading programs using ChatGPT, even without prior coding knowledge. You will gain both AI development skills and financial investment knowledge through hands-on practice covering the entire process, from data collection to predictive model development, stock recommendation systems, and actual automated trading.

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.

This course is designed for developers, AI enthusiasts, and professionals who want to develop real-world AI applications using LangChain, OpenAI, Hugging Face, and Python. Rather than focusing solely on theory, this course takes a practical, project-oriented approach. Throughout the course, students will directly build a total of 15 high-quality AI applications, including chatbots, CSV analysis tools, resume screening systems, invoice extraction bots, support assistants, marketing tools, and text-to-SQL applications. I created this course to make complex AI concepts easy to understand and to ensure modern LLM development is accessible to everyone. Many learners struggle to understand how tools like LangChain, embeddings, memory systems, vector databases, and AI agents interact in real-world applications. This course guides you step-by-step through clear explanations, hands-on coding sessions, and actual implementation workflows. By the end of the course, students will confidently understand how to design, build, and deploy AI-powered applications using the latest generative AI technologies.

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

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

"The deep learning code runs, but why do the formulas in papers look so unfamiliar?" As you study AI, you eventually hit a wall of mathematical formulas. If you trace the source of that wall, it usually leads back to not having a solid foundation in the most basic mathematical language. Starting with the language of sets, this course covers core concepts across 18 lectures, including equations, functions, sequences, exponents/logarithms, and trigonometric functions. We don't make you memorize formulas. While we briefly touch upon how these connect to the context of AI, the primary goal of this course is one thing — to build an unshakable foundation for when you later learn linear algebra, calculus, and probability/statistics. As the first part of the Suminjeongeum series, this course will provide you with the common language needed to properly digest the remaining three parts.

Learn Pandas' core features, comparing with SQL!

“I have the data, but I don’t know how to look at it.” This is the most common concern for those starting on-chain analysis for the first time. In this course, a 10-year veteran data analyst and on-chain researcher fully reveals all the tools and interpretation techniques used in actual market analysis. ㆍWhich indicators react first before coin prices move ㆍWhether whales are accumulating or dumping ㆍHow to read market sentiment through bridge and stablecoin flows ㆍHow to extract data via Etherscan and Dune without programming ㆍAnd the interpretation patterns and strategies used by professional analysts This course is designed to help you go beyond "just looking" at on-chain data and build an analytical framework that leads to actual investment decisions.

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

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

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.

The "How Far Can You Go with ChatGPT?" series: Creating a Stock Auto-Trading Application and Web Investment Reports!

SQLD, where do I even start? This course is for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

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 for both beginners who have never been exposed to programming before and those who have some theoretical knowledge about Python. The main purpose of the course is to create interest and enjoyment in Python based on real projects. I hope that through this course, you will gain more ideas and have more fun with Python.

"Smart Factory—it sounds cool, but can't quite picture it in your head?" The news talks about the 4th Industrial Revolution and AI factories every day, but when you actually look for information, it's full of "alien languages" like PLC, MES, ERP, and Edge Computing. What non-majors need isn't a complex circuit diagram, but a 'map' that shows how the whole system works. This course strips away difficult engineering jargon and explains everything about smart factories through intuitive illustrations and analogies that anyone can understand.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.

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.