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

We will create 8 Android apps using Kotlin syntax. Beyond 8 practical exercises, you'll learn Android with diverse theoretical explanations.

This is a basic Kotlin grammar course. Designed for those wanting to develop Android apps in Kotlin, it offers an enjoyable way to build a solid foundation in Kotlin grammar from scratch.

How about moving away from XML-only Android development and introducing Jetpack Compose?

Introduction to Jetpack (JETPACK) for Android development with Kotlin. You can practice various techniques that can be used while developing Android apps.

This course is for developers who have already used programming languages (Java/Python/Swift/Kotlin, etc.). It is a lecture designed to quickly learn JavaScript in one hour. Although we are in an era of coding with AI, human developers must supervise AI code. Therefore, this lecture aims to quickly build the minimum knowledge needed for supervision.

This is an online class that can help you create a portfolio while preparing for employment as an Android developer.

We'll go through a simple tutorial and hands-on practice with Circuit, an Android Jetpack Compose framework.

This is an Android development theory for creating a portfolio app for employment (job change).

Let's create a plausible app with Jetpack Compose. Let's advance the example a little and connect the API (Firebase) to do 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 your designers, “This doesn’t work on mobile.” Jetpack Compose makes it easy to implement UI/animations.

Jetpack for Android Dev with Kotlin: An Introduction. Covers LocalDB/Network communication.

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.

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

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.

You can use Python to analyze large amounts of data and visualize the analyzed data in graph form so that you can easily understand it at a glance.

If you're just learning Python and don't know what you can do or what you should do? Let's learn how to use web technologies with Python, such as web crawling, automation, and APIs.

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.

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

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!

Through this lecture, you can learn about understanding SQL and databases, SQL syntax, database design for practical application, database utilization through programming, and even data analysis application cases.

Building Your Own Data Analysis Portfolio with Free GEMINI CLI Vibe Coding Data Collection, Analysis, Reports, and Dashboard Creation for Work Automation Even if you're new to data collection, by learning the principles, prompt writing methods, and VSCode usage, you can perform data collection, analysis, visualization, reports, and dashboard creation like a data analyst. From Python Data Collection to Analysis Report Writing with GEMINI CLI and VSCode Prompt Writing and Error Resolution Methods for Foolproof Data Collection and Analysis

I will guide non-majors and beginners to quickly pass the Big Data Analysis Engineer practical exam! Theory lightly, practice thoroughly. Even without complex background knowledge, focusing on past questions, we intensively study only the points sure to appear on the exam.

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

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.

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

Let's develop specialized skills in programming skills, algorithm skills, and statistical analysis skills!

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 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.

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

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.

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