PYTHON like MATLAB

This is not a complete list of Google Spreadsheets, but rather a collection of only the things I use to preprocess data in my field.

I wanted to briefly cover the basics of Python through Jupyter Notebook, which allows you to immediately check the results of your coding.

This is a [Data Analysis, Programming Language] lecture prepared for SQL data analysis beginners. This is a SQL SELECT basic grammar lecture that starts without installing SQL.

You can learn how to handle data frames (tables) using Python, similar to the SELECT statement in SQL.

I have summarized the essential SQL SELECT statements and basic usage of Google Sheets that I learned while working as an analyst at a service company.

This is a basic SQL SELECT grammar lecture that starts without installing SQL.

This course covers the most important and basic grammar in MATLAB through simple examples, so that even non-computer experts can learn it quickly.

Python, now you're doing it? Then, can you implement GUI using PyQt in Python? In order to implement GUI using Python, I've included only the most necessary content, focusing on the most frequently used syntax in actual development sites, utilizing the package PyQt.

You will learn how to develop data/machine learning web applications through 5 practical projects. You can easily and quickly build and deploy web applications with Python and Streamlit. (Updated in June 2025)

A DBA instructor with 30 years of experience teaches 45 essential SQL tuning techniques that can be immediately applied in practice through real-world examples. Master the practical know-how to make slow queries 10 times faster, from execution plan analysis to index optimization and join tuning!

From Python fundamentals to practical data analysis! You will learn practical Python skills for processing, visualizing, and analyzing data while solving business problems.

This class will teach you what effects you can get when you introduce Python into a website created in WEB1.

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

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.

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!

Learn the basic grammar of the Python language, practice writing simple logic using it, and learn about various libraries.

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.

In this course, you will learn how to program kernels and develop PyTorch modules. You can use the knowledge you have gained to develop models faster.

You will learn techniques that can be applied in various fields of IT security, starting from the introduction to Python programming.

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.

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.

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

Learn Python coding. Learn design scripting with Rhino3d Grasshopper. Learn creative coding such as computational thinking, parametric, and generative design.

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

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!

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.