MariaDB client development, HeidiSQL

We will look at usage and examples of the 108 main internal functions provided by MariaDB using the HeidiSQL development tool.

Secrets of people who are good at their jobs! How should I start with SQL? It covers everything from SQL installation and basic environment configuration to simple practical exercises that can be used in real life! You can also learn basic commands step by step through practical exercises.

A beginner's guide to SQL coding! We'll teach you the secrets of writing, interpreting, and validating SQL.

By implementing various practical data analysis cases using SQL, you can simultaneously improve your data analysis and SQL utilization skills.

This course will solidify the basics of SQL through various problems that can be encountered in the actual IT industry. Solve the problem-solving quests, take the first step toward data analysis, and strengthen your SQL skills that can be applied in real life!

This lecture is a lecture on database basics in the [Web Development Full Stack Course] lecture series for training full-stack web developers. This lecture is a process of understanding database design while analyzing Netflix and Carrot Market. It is a basic lecture where you can learn basic database design principles and SQL.

Systematically learn the distributed NoSQL database Cassandra, from basic concepts to practical application. Develop high-volume data processing capabilities through practice-oriented theory and hands-on exercises, including data modeling, query optimization, and cluster configuration. Even without prior database experience, you can grow into a Cassandra expert based on the know-how of a current Silicon Valley developer.

Starting from installing MariaDB and understanding its structure, you will learn step-by-step from writing SQL queries and utilizing functions to joins and subqueries. You will master core practical features such as table design, performance management, backup, and recovery through hands-on practice, completing the practical skills necessary for database development and operation.

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.

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.

If you want to be recognized as a machine learning expert in large-scale data environments—from understanding the core framework of Spark Machine Learning to SQL-based data processing through high-difficulty practical problems, and the ability to implement optimized machine learning models through business domain analysis—join this course.

Learn common components of global-scale services through popular papers, books, and articles.

This course teaches you how to build a practical Unity game with a database. It covers difficult-to-access topics in an easy-to-follow lecture format.

Learn how modern data teams leverage dbt. Build maintainable analytics models and validated data pipelines hands-on. Master core concepts of analytics engineering with a practical focus. This course is for those who want to take their data career to the next level 🚀

Perfect preparation for the SQLD certification, from understanding SQL to practical function application, finishing with the latest exam questions!

This is a course for learning MS-SQL through baseball and corporate databases.

This course goes beyond basic CRUD-level database usage, helping you develop the PostgreSQL skills needed in the AI era from a practical, real-world perspective. Drawing on AI development experience in Silicon Valley, you’ll gradually learn how to design and use JSON, indexes, transactions, and pgvector in actual services, while gaining the skills to solve complex data structure and performance problems.

If you can master DB and programming, you should be more than halfway prepared for the information processing engineer exam. Let's take a look at the DB and programming parts, which are worth 45 to 55 points in the practical exam, and pass the written exam steadily.

Channel Talk interviewers will directly analyze the difference between failing and passing answers to the same questions, and help you prepare for actual follow-up questions.

Immutable truths for developers/engineers that will never change even in the AI era! We provide essential computer science knowledge for free to prepare for developer/engineer job applications and technical interviews.