インフラン - ライフタイムキャリアプラットフォーム

There was a rumor that Ediya Coffee always opens its stores near Starbucks. How much of a difference is there really between the store locations of Ediya and Starbucks? Will the real estate price fluctuation trends from 2013 to 2019 be reflected in apartment pre-sale prices as well? What kind of parks are in my neighborhood? How can we best utilize the data available on the Public Data Portal? The goal is to become familiar with Python and various data analysis libraries by working with different types of data through public data.

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.

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.

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.

This is a detailed and practical course for Google Analytics beginners. Rather than just covering fragmented features, you can learn the actual analysis process using GA4 through scenario-based analysis. It is continuously being updated to reflect the latest GA4 changes!

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 designed 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.

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.

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

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.

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.

I have packed this with everything I want to tell junior PMs/POs who are struggling due to a lack of good mentors. I will generously share various techniques and mental models used by high-performing PMs/POs.

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

By skimming through the content covered in the Tableau certification, you can grasp the overall features of Tableau in a short period of time.

This is a course for PMs who want to utilize data. It covers the entire process of using data in a PM role, capturing the full workflow from your first day at a new job to the beginning and end of a project. It is an introductory data course designed to build your thinking power, covering everything from data-driven and logical thinking to metric definition, log design, experiment design, and building a data culture. Although it was created for PMs, the content is also highly beneficial for data analysts (in fact, many analysts have already taken this course). Additionally, many professionals in marketing, design, and business planning roles are also taking the course.

We guide non-majors and beginners to quickly obtain the Big Data Analysis Certification (Practical Exam)! Keep the theory light and the practice solid—focusing on core points that are guaranteed to appear on the exam through past questions, without the need for complex background knowledge.

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.

Based on the key indicators defined based on data, learning through experiments and rapidly iterating to grow the service. This is a 101 lecture covering the basics of growth hacking.

When using Pandas for data analysis, preprocessing, machine learning, and deep learning, we often find ourselves relying on the same core functions. There is a Pandas Cheat Sheet that compiles only these essential features. For those who have grown tired of trying to learn Pandas through thick books, this two-page document will teach you Python Pandas. Master the core functions of Pandas using the cheat sheet provided by the official Pandas tutorial.

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

Let's learn together about Columnar Storage, which allows you to conveniently handle both structured and unstructured data provided by GCP and allows for a free table format, and BigQuery, a universal database.