MongoDB - NoSQL DB Learned with JavaScript

Build a web service from start to finish with Ruby

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

In an era where flexible data processing beyond the limits of SQL is required, learn everything about MongoDB. From NoSQL concepts to installation, CRUD practice, aggregation pipelines, text search, and indexing, you will learn step-by-step and complete your practical skills through Python crawling integration and container environment construction.

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.

Learn how to analyze 5 million Korean apartment transaction data using PostgreSQL. Covers the process of data cleaning, transformation, and deriving meaningful insights through various SQL queries.

This is a SQLite lecture provided by Living Coding (Open Tutorials), which will help you get started with the relational database SQLite.

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.

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.

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

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

If you work with data, SQL is a fundamental skill you must know. In this course, we will learn SQL from a data analysis perspective, focusing on hands-on practice. The practice will be conducted in Google Colab using DuckDB.

This course provides a step-by-step learning path, ranging from the fundamental usage of MySQL to advanced techniques required in real-world production environments. It covers a wide range of topics, including data modeling techniques based on various case studies and practical data, evaluating the effectiveness of Foreign Key designs, analyzing Google Calendar schema DDL, and modern DDL design principles. Through this course, you will gain an in-depth understanding of how to utilize MySQL as a core system component rather than just a simple database.

This is a course on creating practical Unity games with databases. It covers topics that are usually difficult to encounter, explained through lectures.

You will learn how to analyze and quickly visualize various types of data using the Python Streamlit library and output it as a web service. You can use it when you want to apply it to your work faster than the existing web development method.

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.

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

This course goes beyond simple CRUD-level database usage to help you acquire PostgreSQL skills necessary for the AI era from a practical perspective. Based on AI development experience in Silicon Valley, you will learn step-by-step how to design and utilize JSON, indexes, transactions, and even pgvector in real-world services, while mastering methods to solve complex data structures and performance issues.

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.