From pytest Basics to Practical Application: FastAPI Testing and GitHub Actions CI

This course covers the fundamentals of Docker in 7 lessons totaling 3 hours and 55 minutes. Rather than stopping at conceptual explanations, you will write and build 5 Dockerfiles yourself. By the end, you will combine a FastAPI server and a MySQL database into a single application and run it with one line: docker compose up. Lessons 1 and 2 begin with installing Docker Desktop and checking the WSL2 environment. You will pull an ubuntu image from Docker Hub and confirm that images are composed of multiple layers, then manage local images with images and rmi. Next, you will work with the container lifecycle using run, ps, stop, and rm, and use exec to enter a running container. You will open an httpd container’s web page in a browser through port mapping (-p), then start a MySQL container with a volume (-v) and environment variables (-e) to see why data remains even after the container is deleted. Lessons 3 through 5 focus on creating images yourself. You will examine FROM, WORKDIR, COPY, ENV, RUN, CMD, and EXPOSE line by line, highlighting the difference between RUN and CMD: RUN operates at build time, while CMD operates at runtime. You will create images for four different types: a Python script that runs once and exits, a continuously running FastAPI server, an executable compiled with PyInstaller, and an existing binary such as jq. In the compilation example in particular, you will use a multi-stage build to discard the build tools and keep only the final output. Lessons 6 and 7 focus on connecting containers. First, you will reproduce the "Internal Server Error" that occurs when two containers are started without network configuration. Then, you will create a network with docker network create so that the containers can find each other using only their names. You will check the assigned IP addresses with network inspect and even visually confirm that Docker’s built-in DNS (127.0.0.11) is working by using ping and /etc/resolv . conf inside a container. In the final lesson, Lesson 7, you will transfer all the docker run options covered so far into a single compose.yaml file, then bring up and shut down the entire application with up and down. The five types of project materials used in the exercises—including Dockerfile, app . py, and compose.yaml—are provided, so you can follow along immediately without typing. The exercises are conducted in a Windows + PowerShell environment, and the commands are the same on macOS and Linux.

In this course, you will learn NodeJS, which allows you to develop backends using the Javascript language, and develop API servers using NodeJS using the test-driven development (TDD) method. You will also understand the basic principles of ExpressJS, a representative web framework for NodeJS, and learn how to develop REST APIs used in mobile and web services.

Beyond traditional Jenkins-based CI/CD, this course also covers GitOps deployments using ArgoCD. You will design and implement CI/CD and GitOps deployment strategies for dev, staging, and production environments by combining Jenkins and ArgoCD. You will work with both push-based Jenkins and pull-based ArgoCD, directly comparing the two approaches on the same cluster to build a practical hybrid deployment pipeline. You will practice essential deployment techniques for operations, including Canary, Blue-Green, RBAC, approval procedures, incident response, and automatic rollback.

If you are a student or developer who is using or studying the Java programming language, you will learn various methods of testing your applications that you must know.

This course consists of 41 lessons and approximately 22 hours of training on designing and implementing backend APIs with FastAPI. FastAPI is a framework that is easy to get started with. Skim the documentation, write a few lines, and your API is up and running. The problem comes afterward. If you don’t know how a request travels to reach a function parameter, when dependencies are cleaned up, or where exceptions are caught, you can quickly get stuck as soon as things become even slightly more complex. This course spends time tracing how things work internally. We begin with the development environment. You’ll learn both conda and venv, send requests using the VS Code REST Client and Swagger UI, and become familiar with the structure of HTTP requests and responses. Next, we cover the difference between path parameters and query parameters, explaining why 422 errors occur in connection with type checking. Pydantic is the area explored most deeply in this course. After covering everything from scalar types to dates, UUIDs, Decimal, Enum, and Literal, we move on to BaseModel. We use Field() to define constraints, validate single and multiple fields with @field_validator, and examine the differences between the before and after behaviors of @model_validator. Since the course is based on Pydantic v2, you can apply the latest syntax directly in real-world projects. The middle section focuses on structure and dependency injection. We cover how to split files using APIRouter, how to use functions and classes as dependencies, Sub-dependencies, and decorator-level dependencies in sequence. Four lessons are dedicated to yield. We delve into how generators work, how exceptions are passed back up the call stack with raise, and how exceptions can be injected at the yield point using throw(). Understanding how resource cleanup works in dependencies that include yield makes DB session management much clearer. The latter part covers authentication and databases. We organize the concepts of OAuth 2.0 and its four Grant Types, then implement JWT issuance and verification, the internal execution logic of OAuth2PasswordBearer, and authorization control using Security() and scopes. We then configure Google, Kakao, and Naver clients ourselves and add social login using the Authorization Code Grant flow. Finally, we cover the SQLAlchemy ORM, including the URL structure of create_engine, the roles of the Dialect and DBAPI, transactions, sessions, and model and table creation. This course is suitable for anyone who wants to understand not only "working code" but also "why it works that way.&quot

By developing a simple ReactNative app using the TDD methodology, you will learn the concepts of TDD and practice applying them to ReactNative mobile app development.

This course will help you gain more confidence in the code you develop by learning the basics of testing.

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.

Do you want to effectively use GitHub Actions in real life? This course introduces practical CI/CD scenarios, modularization and version management methods, and also teaches you how to deploy in a cloud environment. Let's learn the most realistic way to use GitHub Actions based on practical experience!

This is a recorded video of the TDD online live meetup held in July 2025.

We will teach you everything from basic concepts to situational test writing methods and advanced testing knowledge so that you can master everything about front-end unit testing.

In this course, you will learn about the general types of front-end testing and how to write reliable tests by selecting the appropriate test for the situation.

Even if you create the same function, the code of a junior developer who has just learned JavaScript syntax and that of an experienced senior developer will be quite different. Of course, even if the results are the same. The reason the latter's code is recognized is because of its well-designed structure and scalability to respond to changes. This lecture will learn about how to create such good code.

From Docker, Kubernetes to microservices, CI/CD, and service mesh, you can easily learn not only the basic theory but also the actual application implementation through examples. By organizing only the core contents necessary for actual use, it provides a starting point for learning about the element technologies covered in the lecture.

A Complete End-to-End Developer Journey — Build Lightning-Fast APIs, Modern Frontend Interfaces, Real Projects, Authentication Systems, Dashboards & Full Deployments Using FastAPI, React, and Vibe Coding Techniques.

The TDD & Clean Code masterpiece lecture, recommended by many senior developers in Korea to junior developers for over a decade.

Build an AI agent from scratch using Python and a single while loop, without any frameworks. In the introductory section, you’ll add tool design, failures and costs, memory, human approval, evaluation, and a web interface one by one to complete a small coding agent. In the hands-on section, you’ll implement RAG, multi-agent systems, and an MCP server yourself using real business reports from DART, then compare them numerically with LangChain and LangGraph.

Did you give up while studying Spring? Even complete beginners new to coding and non-majors can make it from JSP to Spring Boot without giving up - we'll open the path to Spring Boot for you.

SonarQube | SonarCloud | SonarLint – DevOps + Security + QA (Most Widely Used Open-Source Tool) SonarQube is a leading open-source platform for continuous inspection of code quality. It performs automatic code reviews using static code analysis to detect bugs, code smells, security vulnerabilities, and maintainability issues across 27+ programming languages.This course is designed with a learn-by-doing approach, enabling you to gain deep, practical expertise in SonarQube and its ecosystem. Audience: This course is suitable for:Freshers, Developers, Project Managers, Architects, QA Engineers, Support Engineers, DevOps, DevSecOps, InfoSec, and Process Engineers who want to master code quality, security, and CI/CD best practices. Fundamentals & Concepts Introduction to SonarQube, SonarCloud, and SonarLint Purpose and benefits of static code analysis Understanding DevOps & DevSecOps use cases SonarQube architecture, editions, versions, and ecosystem Core SonarQube terminologies and metrics Maintainability, Reliability, and Security concepts Installation & Setup Installation and setup of SonarQube using Docker & Docker-Compose Installation and configuration of Jenkins Installation & configuration of Sonar Scanner Setup of build tools: Ant, Maven, Gradle NodeJS, Python Overview of SonarQube UI and navigation Hands-On Code Analysis Onboarding projects into SonarQube & CI pipelines Running code analysis for multiple programming languages Publishing and interpreting analysis results Reporting code coverage, unit and integration test results Understanding and analyzing: Bugs Vulnerabilities Code Smells Technical Debt Complexity Duplicated lines, files, and blocks SonarLint & IDE Integration Installing SonarLint in: Eclipse IntelliJ IDEA VS Code Configuring SonarLint Connected Mode Real-time code analysis and issue detection in IDEs Quality Management Quality Gates and Quality Profiles Creating and managing custom rules & rule templates Enforcing quality standards across teams Failing builds based on Quality Gate conditions Handling and fixing identified issues Administration & Configuration Project administration User, group, permission, and token management Plugin installation and management Security configuration of SonarQube SMTP configuration and email notifications Branding SonarQube UI with company logo SonarQube Marketplace & system details Security & SAST SAST (Static Application Security Testing) fundamentals Security vulnerability analysis SAST integration with CI/CD pipelines CI/CD & DevOps Integrations Integration with Jenkins (Jobs & Pipelines) Integration with GitHub & GitHub Actions Integration with GitLab & GitLab CI/CD Automating quality checks in CI/CD workflows Failing CI/CD pipelines based on SonarQube Quality Gates Advanced Topics Using the SonarQube Web API for automation, monitoring, and data extraction Best practices for enterprise-grade SonarQube deployments By the End of This Course, You Will Be Able To: Define and manage Quality Gates, Quality Profiles, and Rules Analyze code locally using SonarLint Perform secure and scalable static code analysis Integrate SonarQube with GitHub, GitLab, and Jenkins Enforce code quality and security standards across CI/CD pipelines Confidently administer and customize a SonarQube instance