FastAPI Complete Guide

This course is a practical Airflow master program designed to help you understand "why Airflow works this way" and enable you to design and debug data pipelines on your own. It covers everything from Apache Airflow's core mechanisms to detailed theory and hands-on practice involving DAGs, Operators, Hooks, Scheduling, Timezones, Idempotency, and Templates.

From Multi-Head Attention to the Original Transformer model, BERT, the Encoder-Decoder based MarianMT translation model, and even Vision Transformer, you'll learn Transformer inside and out by implementing them directly in code.

This course will help you grow into a deep learning-based computer vision expert needed in the field through in-depth theoretical explanations of Object Detection and Segmentation, along with practical examples at a level that can be immediately applied in the industry.

Through detailed lectures and hands-on practice on the core elements of SQL, we will provide you with a solid foundation to grow into a SQL analysis expert.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

This course is designed to help you learn the use of ksqlDB and its core mechanisms through various hands-on exercises. After completing the course, you will be able to easily and quickly build a real-time streaming data analysis system based on Kafka.

Through in-depth theoretical explanations of Kafka Connect and detailed practical training that can be used immediately in the field, we will help you grow into an expert in building data linkage and data pipelines based on Kafka Connect that are needed in the field.

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.

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

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.

From core theories of Deep Learning and CNN to implementation methods of various CNN models, and practical Deep Learning development know-how through real-world problems, If you want to become a Deep Learning CNN technology expert, join us in this lecture :)

It provides a key guide to understanding the internal mechanisms of Oracle DB architecture and growing as a performance tuning and performance analysis expert.

This course is designed to upgrade your skills as a practical machine learning development expert by implementing the machine learning model of the Home Credit Default Risk competition on Kaggle.

We will help you easily understand the core concepts of machine learning and acquire the ability to implement practical machine learning applications by moving away from theory-based machine learning courses.

'Complete Mastery of Practical SQL in 49 Sessions II - Advanced Course' follows the basic course. By using a practical database for learning, you can apply it right away in the field, and it is structured so that you can fully learn the learning content through theoretical explanations, practice, and solving a total of 200 application problems.

This course is a master class that systematically covers the fundamental principles and practical applications of MongoDB. Starting with core MongoDB concepts, you will systematically learn essential topics for practical work, such as database design, CRUD operations, indexing, aggregation pipelines, performance optimization, transactions, and security. It explains topics step-by-step so even beginners can understand, and you can deeply learn the working principles of MongoDB through exercises and examples. This is the best introductory and practical course for developers who want to build strong MongoDB skills for practical work.

Learn how to use FastAPI that can be applied directly to real-world practice!

The SQLD Latest Past Exam Problem Solving Course is a practical preparation lecture that reflects the 2024 revised exam standards and is based on actual past exam questions. Going beyond simply checking answers, it meticulously covers the question's intent, key testing points, and common pitfalls, developing practical problem-solving skills for SQLD certification success.

In this course, we will practice step-by-step how to use React and FastAPI to implement social features such as real-time voting, comments, and likes, as well as how to monetize by integrating payment systems (Kakao Pay, Toss Pay, etc.).

Learn how to write SQL queries and work with databases using the MariaDB client development tool HeidiSQL.

This course systematically teaches normalization and denormalization, which are core concepts in database design. Learners will understand the necessity and principles of normalization, and acquire step-by-step knowledge from First Normal Form to Third Normal Form and BCNF normalization techniques. Additionally, they will learn denormalization techniques that are essential considerations in practical database design, and discover actual application methods for performance optimization. Furthermore, learners can understand the essence of NULL values and their operational results, which are important concepts in databases, and examine the concept and characteristics of **Artificial Identifiers** to experience the importance of data integrity and management. Through this course, learners can establish a foundation for solving various problems that may arise during the data modeling process and develop database design capabilities applicable to both theory and practice.

Learning by Doing: 정보처리산업기사 I have prepared everything for passing the 정보처리산업기사 course-evaluation practical exam.

This course is designed to systematically teach advanced SQL features, specifically GROUPING functions and Window functions, to prepare for the SQLD exam and enhance practical data analysis skills. You will learn the concepts and applications of GROUPING functions and master methods for analyzing data at various aggregation levels. Understand the basic concepts and types of **Window functions (based on the OVER keyword)** and improve your practical skills through hands-on exercises. Learn **Ranking functions (RANK, DENSE_RANK, ROW_NUMBER, etc.)** and window options for aggregate functions through practical business examples. Cover **Row order functions (LAG, LEAD, FIRST_VALUE, LAST_VALUE, etc.)** and practice time-series and sequence-based analysis firsthand. 👉 Through this course, learners can expand their data aggregation and analysis skills to an advanced level, gaining expertise that is immediately applicable not only to the SQLD exam but also to real-world corporate data analysis environments.

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 🚀

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.

Solidify your foundation in Python/Django web service development. Learning Django takes time, but you can maximize your productivity through iterative development. Turn your imagination into reality.

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.

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

Databases and SQL are essential for backend developers! We prioritize explaining them in an easy-to-understand manner.

SQL data analysis! We will teach you how to solve practical problems that are applicable in the field, quickly and easily!

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

Using the ChatGPT API, develop a full-stack multilingual translator web application in just 30 minutes, and even if you know nothing about AI, try incorporating the latest AI (ChatGPT API) into your product!

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

This course is a practical, hands-on guide to automating repetitive tasks and maximizing work productivity using ChatGPT and Python. You will learn step-by-step how to use AI to automate daily repetitive tasks such as Excel work, report writing, sending emails, and data organization. Starting as a non-developer myself, I have taught AI automation to thousands of students, and I have compiled only the methods that can be used immediately in actual business environments. This course focuses not on complex theories, but on **"automation techniques you can use right today."** 👉 The goal is to turn ChatGPT into more than just a tool, but into **your own personal work assistant (Jarvis)**.