Analyzing and processing data with Python Pandas

You can call, analyze, and visualize data from public data. You can learn how to collect transaction information on all green onions traded in the wholesale market from public data and perform data preprocessing, data analysis, and data visualization.

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 a course to learn data analysis methods using the Pandas library. You will learn practical application methods by learning the library and analyzing sample data in parallel.

Pandas is one of the most widely used libraries in Python. Pandas, which has become an essential element for data analysis, you can learn everything about Pandas, the essential library for Python data analysis, through the <Pandas in One Shot> lecture.

Create Your Own Data Analysis Portfolio with GEMINI CLI Vibe Coding - Start Without Any Charges Data Collection, Analysis, Reports, Dashboard Creation, and Work Automation Even if you're new to data collection, once you learn the principles, prompt writing methods, and how to use VSCode, you can perform data collection, analysis, visualization, reports, and dashboard creation just 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

With Python Quant Investment, you can create investment strategies based on data and invest according to the strategy. You can implement various asset allocation strategies and ultimately create your own investment strategy.

This lecture is a follow-up lecture to 'Python Data-Based Stock Quant Investment Part 1'. If Part 1 was more of an introduction, Part 2 is an in-depth lecture that focuses on the entire flow of practical strategy implementation and quantitative investment development. This class focuses on advanced Pandas techniques for handling time series data, and how to implement signal-based strategies and static/dynamic asset allocation strategies that require adjusting asset weights at various intervals based on this. Furthermore, it goes beyond strategy implementation and learns about 'code framework' that directly verifies and backtests various investment strategies with minimal code modifications, how to extend this to improve it so that it can lead to actual investment, and what to watch out for in this process. In addition to the programming component, you can experience the best Python quant investment flow that you cannot find in investment books, blogs, YouTube, etc. by deeply covering theoretical contents such as the two types of return concepts (simple return, log return) and evaluation indicators related to backtesting.

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?

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.

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.

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.

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

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.

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.

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.

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.

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

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!

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

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

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