인프런 - 라이프타임 커리어 플랫폼

This covers Amplitude, which is being used by leading companies in various industries for user behavior data analysis. It covers everything from creating a demo account to creating and utilizing charts in Amplitude.

SQLD, where do I even start? A course for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

SQLD, where do I even start? A course for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

Solve 88 expected questions for the 'Tableau Desktop Specialist' certification. Practice with Tableau programs directly.

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

Become a pioneer in the latest large language model (LLM) technology through Langchain online lectures! This course provides practical skills and innovative knowledge that will upgrade your career. #LangChain #LangGraph #LangSmith #MCP

How to Read the World with Data: Explore Your Own Data Science! Dive deep and practically into the tools and techniques that form the core of modern data science. In particular, you will learn how to analyze data and implement algorithms using Anaconda, Numpy, Pandas, and Scikit-learn, essential components of data science.

By solving Leetcode SQL problems, you can understand problem types and improve your SQL implementation skills in a short period of time.

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.

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.

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.

There are common patterns in the questions frequently asked on the Big Data Analytics Engineer practical exam. And there are also a few lines of code that you must memorize before going to the test center. If passing the exam is your goal, please make sure to take this course.

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

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!!

Master advanced SQL, solve 101 practical data analysis problems at a professional level together, and build a solid SQL data analysis skillset.

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.

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.

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.

For those looking to learn Data Science, Big Data, and Crawling, (1) we will summarize the most essential Python core syntax in a short time, and (2) you will become familiar with Python and crawling through practical crawling programming.

This course is designed for beginners, students, and those who want to use Polars, aiming to acquire the necessary skills for data analysis, from basic concepts of the Python-based data analysis library Polars to simple data processing and exploratory data analysis (EDA).