Hướng dẫn đầy đủ về Spark Machine Learning - Phần 1

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.

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.

This course is designed to help you learn the core functions of FastAPI, as well as the entire process of web service development. Through this course, we will help you become a FastAPI expert developer needed in the field.

This course will help you become a deep learning-based computer vision expert who is needed in the field by providing a deep theoretical explanation of object detection and segmentation and practical examples that can be used immediately in the field.

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 :)

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.

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.

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

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

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 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 :)

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.

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.

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.

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.

Theory and practice are different. We will understand the basic concepts of machine learning and introduce the core concepts and theories of various models that you must know. And we will share various techniques and know-how that are helpful in practice while handling various data.

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.

In this lecture, you will learn the basic theory of reinforcement learning.

Learn the process of building data pipelines using Apache Airflow from basics to practical application. Understand Airflow's core concepts and architecture, and master advanced design patterns frequently used in practice such as dynamic DAGs, parallel processing, distributed processing, and Custom Operators through hands-on exercises. Set up a practice environment with Python and Docker, and develop practical skills to design and operate real workflows.

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!

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.

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 course is for those who are learning database programming for the first time or those who have some knowledge but want to learn systematically. From concepts to practical exercises, you will master the database query language by organizing examples of types that frequently occur in real life.

We will provide information on 3D spatial information data acquisition and mapping methods using drones, LiDAR, etc., and data visualization tools and techniques based on the application areas of 3D spatial information data, incorporating various case studies.

We introduce methods for planners and marketers without data analysis experience or technical skills to try data analysis at the most basic level, complete with various examples. Built on years of hands-on practice with over 2,000 participants in more than 100 companies and public institutions, the content is designed around the most practical analysis methods for data non-experts.

Let's understand model algorithms for machine learning and deep learning by utilizing Keras!

Through this course, students will learn various reinforcement learning theories and implement them themselves, as well as create a reinforcement learning environment to test the reinforcement learning algorithm implemented using Unity Machine Learning Agents.

SQLD Yellow Book 176 Problem Solving Lecture for You Who Studied but Cannot Solve Problems. After Completing the Course, You Will Become an Expert Beyond Passing. SQLD All-in-One Pass!

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.

This is a basic Python course for starters who want to grow as data analysts. - Those who want to do data analysis but don't know Python - Those who want to learn machine learning with Python - Those preparing for the Big Data Analytics Engineer practical exam - Those who want to develop machine learning-based applications with Python

This course covers everything from the basics to hands-on practice of AI platforms, and is a program where you can learn AI image generation technology. Learners can understand the fundamental concepts of AI and develop the ability to generate AI images using various tools and technologies. Through this course, you can enhance your understanding of the AI field and learn how to directly generate AI images in real-world applications.

It covers basic data concepts, useful R functions and packages, and data analysis exercises, to allow anyone to perform big data analysis using R programming.