Kubernetes Guide for Beginners

This is a Docker guide for beginners who don't know anything about Docker. We focused on helping you quickly learn why Docker is popular and how to use it, without getting into complicated details.

This is a Docker guide for beginners who don't know anything about Docker. We focused on helping you quickly learn why Docker is popular and how to use it, without getting into complicated details.

We cover everything from introduction to utilization of the framework for flexibly running distributed systems in a container environment using “Kubernetes,” an open source virtualization project based on containers.

Packed with LLM Fine-Tuning Know-how, learned from Silicon Valley LLM Project Practitioners.

This is a curriculum full of Captain's personal feelings, an 8-year full-stack developer who fell in love with coding. It is filled with Captain's desire to teach everything about the backend! As you listen to this lecture, you will find yourself thinking, 'Does he really teach this much?' Let's start with this lecture that thoroughly explains even the parts that everyone finds difficult.

Let's implement a web service modeled after Pinterest's unique card-type layout design using Django, Python's representative web framework.

This is not a lecture that simply memorizes commands. It's a practical introductory course that helps you intuitively understand the 'flow' of technology - why containers emerged, how Docker creates and runs images based on what principles. Even if you're encountering Docker for the first time, after taking this course, you'll be able to explain "why containers are a necessary technology" on your own.

Regardless of the field! This is a lecture that covers the core fundamentals that developers must know in practice in an easy + code-oriented way. I highly recommend this lecture to all junior developers and job seekers who want to grow.

This course is designed to help you quickly learn server zero-downtime deployment methods using Nginx, Docker, and Spring Boot through hands-on practice. Learn Blue-Green deployment, which is frequently used in real-world scenarios, faster than anyone else!

Instead of long and boring theories, you can learn them one by one through short practical exercises, and as you flesh them out one by one, you will soon be able to experience the overall architecture composition.

When you're doing backend development, at some point you face this dilemma. As services grow and traffic increases, there comes a moment when simple REST communication and CRUD structures feel limiting. I experienced the same problem in real-world work and went through many trials and errors between performance and structural complexity. The solution I chose in that process was NATS. Its simple configuration based on a single binary, ultra-low latency performance in microseconds, and the fact that it provides just the right amount of essential features for real work—from Pub/Sub to Queue Groups and JetStream—made it a very practical choice in actual service environments. This course is not about listing NATS features. Based on the problems I faced in real work, I explain with code and flow diagrams which situations led me to choose NATS, why, and how I designed the architecture. This is a course designed to help everyone—from those new to messaging systems, to backend developers preparing for jobs, to senior developers contemplating better architectures—understand distributed systems and grow to the next level.

This is a DevOps course based on practical experience in Silicon Valley. It goes beyond theory to cover content that can be applied immediately in the field. You will learn how to develop using Generative AI (Vibe Coding), set up CI/CD tools in a Kubernetes environment, and implement strategies to keep operating costs at $0. We will cover configuring a production environment without additional costs by running DB, Redis, S3, and batch jobs inside Kubernetes, and you will master building automated pipelines using GitHub Webhooks and Jenkins through hands-on projects.

This course is Part 3 of the Full Stack lecture series, designed to help you solidly master the latest server technologies and Docker. The course is structured to enable you to practically incorporate Docker into your tech stack by meticulously testing Docker's various options, learning related technologies such as Linux that are necessary for understanding Docker, and building actual complex services.

A solo IT startup founder and solo entrepreneur's experience distilled into an honest, straightforward, intuitive, and deep React + Spring Boot course (Docker, AWS, GitHub Actions) I just unified everything into this one course.

This course is built from real-world experience designing and deploying production-grade LLM applications on Azure. Rather than focusing on toy examples or isolated notebooks, I guide students through the exact challenges they face when moving from experimentation to real systems: data ingestion, vector storage, service orchestration, cloud deployment, and security. Throughout the course, I break down complex Azure services into clear, practical steps, explain why each architectural decision is made, and show how components work together in a scalable system. Students learn by building, debugging, and deploying a complete LangChain-based application, gaining confidence in solving real infrastructure and application-level problems.

Build a local LLM with RAG-based Q&A system in just 2 hours of hands-on practice using Docker + ollama + R2R framework. (Suitable for in-house/internal Q&A systems, personal portfolios, AI-powered work capabilities, and even commercial services)

Learn from the beginning how to set up a development environment that even an ordinary office worker can easily understand. It is practice-oriented and focuses on students learning various development tools such as Vim, VS Code, Git, Docker, and remote development. You can learn how to build an efficient development environment by learning step-by-step from the basic usage of each development tool to advanced functions.

This is a 'Practical Linux Troubleshooting Course' where you analyze and solve problems together with generative AI, based on a Docker practice environment that reproduces 5 representative failures that occur in actual Linux operating environments. Even those who were overwhelmed about where to start examining problems can learn the problem-solving approach and thought process of field engineers through AI guidance.

Ghost In the N8N - AI Automation Workflow (AI automation flow through the N8N framework) You will gain the foundational knowledge needed for practical work & business automation in the AI era, along with guides you can use immediately in real-world applications!

You can quickly experience the process of deploying a sample e-commerce service to AWS and continuously improving it into a robust and efficient environment.

In this course, you will be able to create a Reddit website from scratch, step by step.