Inflearn - Lifetime Career Platform

This course teaches the fundamental skills needed to learn the entire Python data analysis process for beginners in data analysis. As an e-commerce planner and developer who actively uses data analysis techniques in the field, I designed it to help you easily learn the full Python data analysis process and apply it right away.

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." 🚀

You will learn about the four stages of big data processing [data collection ▶ data storage ▶ data analysis ▶ expression] in a more fun and systematic way through a code lab method consisting of 30% theory + 70% practice 🧑🏻‍🏫

I'll show you everything about how to build servers for stateful services and how zero-downtime deployment works.

From the fundamentals of MySQL usage to the advanced techniques required in real-world service environments, you will learn progressively. The course also covers a wide range of topics, including data modeling techniques based on various cases and practical data, evaluating the effectiveness of Foreign Key design, analyzing the Google Calendar schema DDL, and modern DDL design principles. It provides an in-depth understanding of how to use MySQL as a core component of a system, rather than merely as a database.

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.

mongoDB, NoSQL You hear a lot these days, but is it still an unfamiliar database? Aren't you using it like a relational database (RDS/SQL)? No matter how good the technology is, if it's not used correctly, it will have the opposite effect. That's why we often see cases of failure in using MongoDB. This lecture will teach you everything from basic concepts to practical know-how so that you can use MongoDB as MongoDB-like as possible.

I learned it the hard way, but I want you to learn it easily. I've discarded unnecessary theories and included only the core essentials of SQL. Build your SQL confidence quickly.

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

This course is a practical analysis program that covers everything from Bin data status analysis to Wafer Defect Map pattern analysis and correlation analysis between yield and process parameters, all based on semiconductor manufacturing data. Going beyond simple visualization, you will learn how to classify defect types using pattern similarity analysis and clustering techniques, and how to interpret the relationship between process variables and yield based on data. The focus is on mastering a structural approach to analyzing semiconductor manufacturing data by directly implementing dashboards that can be utilized in real-world operations.

👉 Recommended for those who want to view AI results not as “values that simply came out,” but as understandable judgments. What exactly does AI use as the basis for making judgments? This course structurally explains how data affects AI’s judgments and why data is said to be important. You will learn how AI interprets numerical information and develops criteria for making judgments.

Real-time data processing is now essential, not optional! Learn to handle real-time streaming smartly with Apache Flink. Batch? Streaming? Even complex concepts can be understood easily and quickly. Hands-on practice configuration where you'll get the hang of it by directly working with Kafka and DB integration! In a world driven by data, start first with Flink.

This is a code-lab-oriented course where you will directly build big data or distributed processing system clusters (HDFS, Zookeeper, Spark, Zeppelin) that guarantee High Availability.

"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.

From the core concepts and infrastructure setup of Kafka, Hadoop, Spark, and Airflow to hands-on practice with Java and Python, as well as building production-level pipelines in an AWS environment.

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.

This course is a hands-on program where you will learn the entire process of using Power BI—from importing and preprocessing data to configuring relationships, writing DAX, and creating actual reports and dashboards. In particular, it is designed to reflect the practical exam types for Management Information Visualization, allowing even beginners to simultaneously prepare for both real-world application and certification. Rather than just explaining simple functions, the course covers data preprocessing, visualization, and core measure creation frequently used in business, helping you quickly master the essential workflow within 8 hours.

Spotfire Advanced - Secondary Battery Course is a practical analysis course where you will directly implement product tray-level quality monitoring and integrated process analysis dashboards based on secondary battery manufacturing process data. Rather than simply learning functions, you will learn how to design and build analysis screens to identify the causes of quality anomalies using actual quality and process data. Basic functional explanations are omitted, and the course focuses on understanding data structures and configuring analysis dashboards that can be applied immediately in the field.

This course is a practical analysis program that performs subject characteristic analysis, adverse event (AE) analysis, treatment effect comparison, and statistics-based visualization based on clinical trial data. Beyond simple visualization, you will learn how to understand clinical data structures and implement comparisons between test and control groups, as well as safety and efficacy index analysis, using Spotfire.

This is a concept-oriented course where you learn 'when and why to stream events' rather than just memorizing Kafka syntax. Using a single shopping mall project, 'On-Market,' as a comprehensive case study, you will master the event flows and principles of 10 real-world scenarios—including orders, inventory, notifications, search, and analytics. You will develop the ability to see the entire system, covering everything from topics, partitions, and consumer groups to event sourcing, CQRS, and idempotency.