Pandas for Data Analysis: From Basics to Data Analysis

Datalian's SQL basics lecture with over 10,000 cumulative students and rich online/offline lecture experience. Learn SQL basics theory and solve 10 HackerRank problems together.

Datalian's SQL intermediate problem-solving lecture with over 10,000 cumulative students and rich online/offline lecture experience. We will solve several problems together to practice the SQL intermediate theory.

Datalian's advanced SQL problem-solving lecture with over 10,000 cumulative students and rich online/offline lecture experience. We will solve several problems together to practice advanced SQL content.

Datalian's intermediate SQL lecture with over 10,000 cumulative students and rich online/offline lecture experience. Learn intermediate SQL theory and solve practice problems together.

Datalian's advanced SQL lecture with over 10,000 cumulative students and rich online/offline lecture experience. Learn advanced SQL theory and solve practice problems together.

If you are curious about the various possibilities and future prospects of generative AI, including ChatGPT and Clova X, that can be used for data analysis, come to our seminar this May!

Solve 25 SQL problems of various difficulty levels. This is the Advent of SQL 2024 explanation lecture. Upon finishing the lecture, you can complete the Advent calendar and obtain a badge.

In the cookie-less era, how will marketing change? If you don't know how to start marketing performance analysis, attend the November seminar.

Data analyst job prep: Lost on where to begin? Get hints at this September seminar!

How can data be leveraged in side projects? Hear the stories of 'Geumim' and 'Skull' at this seminar!

How can data be used in content marketing? At this May seminar, you can hear case studies from data analysts on using data from company blogs and newsletters!

How do IT startups make data-driven decisions? At the April seminar, you can hear examples from DataLean and Postype!

Datalian's SQL practical lecture with over 10,000 cumulative students and rich online/offline lecture experience. How is SQL used in practice? Let's become a data analyst who solves problems using real data from Microsoft's Yammer service.

No need for developers! It doesn't matter if you don't know development. I'll show you how anyone can easily install GA4 with just a few clicks.

We will reveal the actual data analysis portfolio of successful job seekers and the portfolio-related questions they received during interviews!

If you are thinking about using data in your work, get some great tips from this seminar.

Did you know that there are different types of data analysts? If you want to know everything about in-house data analysts and consulting data analysts, come to this seminar!

Practitioners who are curious about how other companies conduct funnel analysis, gather here! Meet the case of the global No. 1 alarm app, ‘Alarmy’, with 75 million cumulative downloads.

Are you worried about whether you can become a data analyst as a non-major? Hear from a non-major senior analyst!

If you are worried about where to start and where to start studying because you need to take a SQL coding test to become a data analyst, then come to this seminar!

The fact that you can analyze data more easily and effectively with Python Pandas instead of Excel! Learn the basic functions of the Pandas library and how to use it in practice through financial data analysis.

There was a rumor that Ediya would open a store near Starbucks. How different would the locations of Ediya and Starbucks be? Will the real estate price fluctuation trend from 2013 to 2019 be reflected in the apartment sales price? What kind of parks are there in my neighborhood? How can I utilize the data in the public data portal? The goal is to become familiar with Python and various data analysis libraries by handling various types of data through public data.

This is not an investment lecture. It covers data collection, analysis, and visualization through securities data. It covers various data formats and teaches various text preprocessing techniques. It covers visualization techniques for time series data and methods for expressing scale. It covers several techniques for interpreting stock price data. This lecture is a course that teaches you how to gain insights through data analysis. The content learned through stock price data is organized so that you can apply it to collecting, analyzing, and visualizing data such as demand, inventory, sales, and traffic volume, where time series is used.

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.

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.

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.

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.

Learn how to collect data from the web and create a supervised learning model for machine learning!

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>.

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.