Super-easy, super-fast data collection (Python crawling)

This is an introduction to Jetpack for Android development with Kotlin. It mainly covers LocalDB and network communication.

This is a course that can help you create a portfolio while preparing for a job as an Android developer.

We will conduct a brief tutorial and hands-on practice regarding Circuit, an Android Jetpack Compose framework.

This course is designed for developers who already have experience with programming languages (such as Java, Python, Swift, Kotlin, etc.) to quickly master JavaScript in just one hour. In an era of coding with AI, human developers must still supervise AI-generated code. This course is intended to help you rapidly build the essential knowledge required for that supervision.

This is Android development theory for creating a portfolio app for employment (or career transition).

We will create a decent app using Jetpack Compose. Going a step further from basic examples, we will connect an API (Firebase) and even implement network communication.

This is a fast-paced development course for busy planners. You can learn the entire development process by developing web front-end, back-end, and DB yourself with simple explanations.

Stop telling designers, "This doesn't work on mobile." You can easily implement UI and animations with Jetpack Compose.

Shall we move beyond Android development using only XML and introduce Jetpack Compose?

This is an introduction to Jetpack for Android development with Kotlin. You can practice various techniques that can be used while developing for Android.

This is a basic Kotlin syntax course. It is designed for those who want to develop Android apps using the Kotlin language, and you can enjoy learning Kotlin syntax thoroughly from the basics.

We will create 8 apps while learning how to build Android applications using Kotlin syntax. In addition to the 8 hands-on practice materials, we will study Android through various theoretical explanations.

You will learn how to collect and manage all stocks listed on the stock market. Through automation, you will collect stock prices daily and even create a dashboard using Shiny to identify stock trends by industry.

Using pandas, we will learn data processing patterns that frequently appear in real-world situations and analyze the processed data.

Learn about Python and how to automatically collect Naver news titles and stock data from Naver Finance using Python. The library I mainly use is BeautifulSoup.

Advanced Selenium course that is not blocked on large platforms Developing a bot that moves like a human

You can easily learn how to collect and process data using Excel's Power Query feature, even if you don't know coding. You will learn Excel crawling skills by practicing the project below together.

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.

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.

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.

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

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.

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!

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

"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.

This course focuses on developing practical visualization skills that can be immediately applied in the workplace by utilizing Seaborn, a core tool for data visualization, and plotly/Dash for building interactive dashboards. Through various hands-on exercises, you can enhance both your ability to create insight-driven visual materials and implement web-based dashboards.

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.

If you're planning to learn Python, pay attention to this course!!! It's completely free~ I highly recommend it for preliminary learning before taking formal courses or starting personal study.

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

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.

"From the basics to 7 domain projects, completing the A to Z of deep learning (41 lectures in total)." Go beyond simply calling models and learn how to build clean, efficient deep learning pipelines using PyTorch Lightning, the current industry trend. Grow into a confident AI engineer capable of handling any data by directly implementing 7 projects, ranging from stock price prediction to generative AI, medical imaging, and sound analysis.

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems