Web data collection techniques used in practice (Web Crawling)

"Following trends is important, but unwavering fundamentals create real skills" This course is an introductory program that helps you understand the flow of data science and properly learn the most practical techniques first.

I will make it so that you can crawl freely. Most of the lectures are conducted through live coding. Please follow along line by line while I code!

Build basic R programming skills and learn basic crawling techniques. We will explain each line while writing the code yourself.

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.

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 is not an investment lecture. It covers data collection, analysis, and visualization using stock market data. You will work with various data formats and learn various text preprocessing techniques. It covers visualization techniques for time-series data, methods for representing scales, and several techniques for interpreting stock price data. This course is about learning how to gain insights through data analysis. It is designed so that the concepts learned through stock price data can be applied to collecting, analyzing, and visualizing other time-series data such as demand, inventory, sales, and traffic volume.

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 is designed for beginners and consists of easy explanations and various hands-on projects. It covers data collection using web crawling and LangChain tools, and summarization, extraction, sentiment analysis, and recommendation systems using LLM.

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.

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.

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