인프런 - 라이프타임 커리어 플랫폼

Anyone can learn data analysis with Chat GPT. You can learn how to apply it in practice through various analysis exercises. (Absolutely!! ChatGPT paid version is required!)

This is a basic course on Python Excel programming that you can learn with the xlsxwriter tutorial. You can analyze data and automate tasks using Python and Excel.

This is a basic/introductory course on digital marketing. It covers how to design digital marketing based on data and various practical cases. It contains stories and content that I want to share from my 14 years of experience in various fields of marketing, from digital marketing agencies to in-house marketers at large corporations. It is recommended for those who want to understand digital marketing in general.

Financial data such as stocks, exchange rates, coins, real estate, and bonds are easily accessible and provide us with opportunities to make money, but most people miss valuable opportunities because they do not know their characteristics and how to handle them. Through this lecture, you can learn how to understand the meaning of various financial data and how to analyze them using Python.

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 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.

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

When you use Pandas for data analysis, preprocessing, machine learning, and deep learning, you tend to use only the functions you use frequently. There is a Pandas Cheat Sheet that collects and organizes only these essential contents. For those who get tired of learning Pandas from a thick book, we will teach you Python Pandas with just two pages of documents. Learn the core functions of Pandas with the cheat sheet provided in the official Pandas tutorial.

Author's direct lecture for the SQL200제 book published by Jeongbomunhwasa! So far, numerous data analysts have gained wings in their data retrieval skills with Instructor Yooyeonsu's SQL lectures.

This is an introductory BigQuery (SQL) course for beginners. Recommended for those curious about data processing methods. We teach SQL from a data analysis and data engineering perspective rather than a backend development perspective.

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.

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

A theory-practice QGIS course covering analysis basics, advanced functions, and visualization introduction for QGIS utilization. Start QGIS by taking this unprecedented all-in-one course!!

Train SQL queries with 50 diverse problems, preparing for real analysis environments and coding tests. * If you're new to SQL, taking the SQL [Concepts Course] first will help you follow along easily.

Train SQL queries through 50 diverse problems and prepare for real-world analysis environments and coding tests. * If you are new to learning SQL, you will be able to follow along without difficulty by first taking SQL [개념반].

Learn Pandas' core features, comparing with SQL!

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.

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>.

We will apply it in practice by crawling sites such as Naver, Amazon, Twitter, YouTube, Facebook, Instagram, and unsplash.com.

From basics to advanced data analysis! Based on what you've learned, analyze data yourself using data from Jeju Island!