Collecting public data to analyze and visualize green onion prices

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.

Excel VBA helps you use Excel faster and more efficiently. Now, learn VBA to spend your free time at work. For web data collection, please refer to this course: https://www.inflearn.com/course/python-crawling#

Building and Refactoring Spring Framework with IntelliJ Gradle Building a Spring Framework development environment and applying the build!

This course is for those who have learned the basic grammar of Python and will learn the core skills used in text data analysis. I hope that those who are interested in text analysis will gain more ideas through this course and use it for a long time.

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.

Son Heung-min's 100th goal project! Practical crawling & data analysis of Transfermarkt

* 100% Practical Curriculum: Focused on hands-on data handling rather than grammar-based learning * Essential Machine Learning Prep: A complete summary of data preprocessing techniques required before AI training * Data Analysis Tool Mastery: Conquer core functions of Numpy (numerical operations) and Pandas (data manipulation) * Deriving Visualization Insights: Transferring data visualization skills using Matplotlib and Seaborn * Building Statistical Foundations: Learning basic statistics and group analysis techniques to identify data characteristics

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.

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>.

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

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.

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

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

We guide non-majors and beginners to quickly obtain the Big Data Analytics Engineer practical certification! Theory lightly, practice thoroughly - even without complex background knowledge, we focus on learning only the essential points that appear on the exam, centered around past exam questions.