인프런 - 라이프타임 커리어 플랫폼

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.

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 a course for PMs who want to utilize data. This course covers the entire process of utilizing data in the PM role, including the flow of work from day 1 of a job change through the start and end of a project. It is an introductory data course that covers data-driven thinking, logical thinking, metric definition, log design, experiment design, creating a data culture, and more, to help you develop critical thinking skills. Although created as a course for PMs, it is structured with content that data analysts would also find beneficial (in fact, many analysts have taken the course). In addition, many people in marketing, design, and business planning roles are also taking the course.

Learn about the basics of Python required for data analysis, the data analysis framework (pandas), and the data analysis process.

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.

Do you want to create a tool that can help you with your real-world investments using Python? In this course, you will learn how to create an interactive web dashboard for financial data analysis for intermediate Python users and learn about pair trading strategies for in-depth quantitative work. We hope that you will be able to create your own useful analysis tools to help you analyze financial data more powerfully and make wise investment decisions.

Leverage Python to create your own indicators and a convenient tool for securities analysis!

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

This is a lecture on how to use NumPy and practice its application in real-world scenarios.

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 structured 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.

We conduct app log analysis using data from Google Analytics 4 and Firebase. It includes useful content for practical use, such as arrays, window functions, funnels, retention, Google Sheets, and more.

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.

By implementing various practical data analysis cases using SQL, you can simultaneously improve your data analysis and SQL utilization skills.

Through detailed lectures and hands-on practice on the core elements of SQL, we will provide you with a solid foundation to grow into a SQL analysis expert.

You will be able to extract the data you want directly without the help of a developer. We will provide everything you need for analysis, from simple queries to joins. Start learning SQL with a direct lecture from the author of the book <Planner's SQL>.

This course will help you understand the analytical capabilities and technologies required for decision-making by managers in the digital transformation era and apply them in actual work.

This is a lecture on data visualization using the Matplotlib library.

Inflearn cumulative students over 30,000, Datarian's SQL basics course with rich online/offline teaching experience. Learn SQL basic theory and solve 10 SQL problems together.

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.

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.