인프런 - 라이프타임 커리어 플랫폼

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

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.

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.

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.

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

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 specific and practical course for Google Analytics beginners. Instead of focusing on fragmented features, you can learn the practical analysis process using GA4 by conducting scenario-based analysis. It is continuously being updated to match the latest GA4 revisions!

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.

From the core of Kafka to in-depth content on internal mechanisms, the course is structured so that even beginners can quickly reach the expert level through detailed theoretical explanations, hands-on practice, and practical Kafka application development practice.

No more encyclopedia-like lectures from A to Z! A reference lecture that only collects the best that can be applied directly to real life!

This course will teach you how to understand the internal operations, monitor, and troubleshoot based on cases that are essential for operating an ElasticSearch cluster. Through this course, you will be able to operate an ElasticSearch cluster more stably.

We will cover Amplitude, currently used by leading companies in various industries for user behavior data analysis. This includes methods for creating a demo account, as well as generating and utilizing charts in Amplitude.

With the advent of the AI era, building data pipelines has become a core competency that determines a company's competitiveness. Learn how to build efficient data pipelines using Airflow, the most widely used tool, directly from a Silicon Valley expert (formerly Head of the Data Team at Udemy, currently a professor in the Data Masters program at San Jose State University) with practical experience and extensive lecturing experience.

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).

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.

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.

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.

The Scala course provides essential skills and knowledge for professionals working in the fields of big data and data science, offering an excellent opportunity to learn efficient data processing and analysis methods through Scala's powerful programming language capabilities. Scala is widely used in big data processing tools like Apache Spark, and through this course, participants will be able to acquire advanced skills required in the big data ecosystem, thereby enhancing their competitiveness. For developers and data scientists who want to build a successful career in a data-centric world, this course will be a crucial learning opportunity not to be missed.

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.

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