인프런 - 라이프타임 커리어 플랫폼

This is a code lab-based class where you will directly build a big data system or distributed processing system cluster (HDFS, Zookeeper, Spark, Zeppelin) that guarantees high availability.

We have gathered Apache Kafka application programming knowledge used in real environments! We will take a look at and practice various functions of Apache Kafka that are key to building data pipelines.

Learn Elasticsearch, the core technology for data search and analysis in the rapidly growing IT field! We will teach you how to solve complex searches simply, along with hands-on practice that you can apply right away. Are you ready to upgrade your digital skills?

You will learn how to write queries against large amounts of data using MongoDB.

This is a course to learn about Airflow, an Orchestration tool for efficiently building and managing data pipelines. Welcome to the Airflow Master Class, where even beginners can learn step-by-step!

SSIS, SSAS, MachineLearning, BI, ETL. You can learn important technologies that cannot be found in domestic books, YouTube, lectures, blogs, and academies. I also recommend it to those who are interested in employment at domestic large companies, American large companies, and American state funding agencies.

By the end of this course, you will be able to implement Apache Spark projects in your organization.

"Big Data + AI Full Stack Development" - The process of building big data that breathes life into AI is carried out in the form of a pilot project. We identify requirements, configure the platform step by step, and perform smart car data exploration and analysis.

Apache Superset is an open-source BI tool that lets you quickly create charts and dashboards by connecting multiple databases. You can visualize data without knowing code, and SQL Lab allows you to run queries directly, making it useful for everyone from beginners to professionals. The dashboards you create can be shared immediately with permission settings, making it perfect for collaboration. Learning Superset gives you the ability to make data-driven decisions quickly and build practical dashboards you can use right away at work. In short, it's perfect for anyone who wants to make data "speak." 🚀

Numpy and Pandas are the foundation of data analysis and the backbone of AI frameworks, and I've packed this course with the core practical know-how I've accumulated through my work and teaching experience. I've designed it with a hands-on approach so that marketers, planners, and beginner analysts can easily follow along with data cleaning and processing—the areas where they most often get stuck. Through this course, anyone can develop the skills to handle data and produce analysis results on their own, without needing help from developers.

Introduces methods for utilizing GA4 data in Bigquery. Using the GA4 Bigquery demo data publicly available in Bigquery from the Google Merchandise Store (https://www.googlemerchandisestore.com/), we introduce methods for marketers and planners to easily utilize GA4 Bigquery data, along with hands-on practice of basic SQL queries.

A DBA instructor with 30 years of experience teaches 45 essential SQL tuning techniques that can be immediately applied in practice through real-world examples. Master the practical know-how to make slow queries 10 times faster, from execution plan analysis to index optimization and join tuning!

This course teaches Python-based text mining: basic theory and practice. It covers fundamental text mining data analysis for practical or thesis writing.

Analyze over 40 types of economic indicators and stock data with AI to create your own powerful stock price analysis model that predicts not only S&P 500 and QQQ ETF, but also individual stocks!

Students who want to learn Hadoop and Big Data will celebrate the amazing advancements in experiencing the world of Big Data through this course!

What is Apache Kafka? How does Apache Kafka work? What are the concepts of Apache Kafka? If you are curious, choose this course😎

Learn why and how to handle data exploration (EDA), data cleaning, scaling, outlier handling, log transformation, and categorical encoding in real-world applications. You will also learn how to merge tabular data and process (unstructured) time series data.

You will develop the ability to define problems based on data and clearly explain the rationale and decision-making process behind them. Additionally, rather than focusing solely on the performance of a single model, you will acquire a pipeline-oriented mindset that evaluates the completeness and reliability of the entire machine learning workflow. Furthermore, you will strengthen your problem-solving skills by tracing back the causes of errors when they occur and deriving improvement directions, and through end-to-end project experience, you will acquire practical ML pipeline capabilities that can be immediately applied in real-world settings.

This course covers everything from core recommendation system algorithms to practical implementation. - Content-based filtering - Collaborative filtering and deep learning-based recommendation model implementation - Two-step recommender systems implementation - Hands-on practice using PyTorch/RecBole - Industry know-how and recommendation result visualization

You can learn the core concepts of GA4 (Google Analytics) e-commerce setup, which is too difficult to learn on your own by searching the internet, through hands-on practice. Performance marketers and beginner developers who are setting up GA4 e-commerce for the first time can easily understand by practicing step-by-step setup on a cafe24 demo shopping mall. Since the developer's role is handled by chatgpt during the practice, marketers and PM/planners without specialized development knowledge can also learn about GA4 e-commerce setup.