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Backend Design Basics for Handling AI - SpringBoot SNS Edition

This is a practical backend course that develops the thinking skills needed to plan and design services, which developers should have in the AI era.

100 learners are taking this course

Level Basic

Course period Unlimited

  • apiece
AI 활용법
AI 활용법
백엔드
백엔드
스프링
스프링
설계
설계
데이터베이스
데이터베이스
PostgreSQL
PostgreSQL
Spring Boot
Spring Boot
DBMS/RDBMS
DBMS/RDBMS
Redis
Redis
s3
s3
AI 활용법
AI 활용법
백엔드
백엔드
스프링
스프링
설계
설계
데이터베이스
데이터베이스
PostgreSQL
PostgreSQL
Spring Boot
Spring Boot
DBMS/RDBMS
DBMS/RDBMS
Redis
Redis
s3
s3

What you will gain after the course

  • Experience Designing Twitter Backend Services

  • Judgment on what tasks to assign to AI

SNS Home

Media

Timeline

Design the backend
and build a real SNS service with AI

Twitter Clone Coding with Spring Boot!


In the AI era, a developer's capability depends on 'design'.
Beyond vague AI code generation, we'll help you build solid backend design skills, from planning services yourself,
structuring data, to the ability to give precise instructions to AI.


In the AI era, backend design is
the ability to properly utilize AI.

Using core technologies like Spring Boot, Redis, PostgreSQL, S3, and more,
you'll directly design and implement authentication, follow, posts, and timeline features.

Beyond simple tutorials, you'll build an SNS service like Twitter from start to finish.
You'll experience all core features including sign-up, login, post creation, and timeline viewing..

Beyond AI utilization skills, you will develop backend system design and implementation capabilities at an actual service level
and gain deep, practical experience that can be immediately applied in real-world settings..

A Practical SNS Project
to Handle AI and Develop
Backend Design Skills

Section 1 - Course Introduction and Learning Objectives

This section introduces an overview of the course that strengthens backend design capabilities needed in the AI era. The goal is to build an SNS using Spring Boot, and to develop efficient utilization of AI agents and code judgment skills.

Section 2 - AI Agent Development and Utilization

From selecting AI agents to developing features using Claude Code and setting up v0 frontend, this covers the entire process of AI-based backend development. Learn how to utilize AI agent skills, hooks, sub-agents, and commands.

Section 3 - Implementing User and Authentication Services

Implement user registration, login, and session management features using Spring Security and Redis. Improve user authentication handling and consider the trade-offs between in-memory and centralized session storage. Additionally, gain backend design experience by implementing an authentication service from scratch.

Section 4 - Follow Service Design and Implementation

Design follow relationships between users and optimize follower/following count queries. Resolve concurrency issues (race conditions) and complete the follow service through database selection and implementation including PostgreSQL, MySQL, etc.

Section 5 - Post Service Design and Implementation

Design various post-related features such as posts, replies, quotes, and reposts from normalization/denormalization perspectives. Implement like and view count features while learning solutions to handle read/write load issues.

Section 6 - Media Service Design and Implementation

Design a media domain using object storage (S3, RustFS) and implement upload and retrieval flows. Learn efficient media delivery methods using CDN and how to establish media-to-post relationships.

Section 7 - Timeline Service Design and Implementation

We analyze the characteristics of timeline data and build a real-time timeline by applying a fan-out architecture. We complete the timeline service through appropriate data structure selection and efficient post creation and display strategies.

Section 8 - Wrap-up and Further Learning

This lecture summarizes the backend design and implementation process covered in the course, presents additional improvement tasks and learning directions for the future, and concludes the lecture.

Building Backend Skills in the AI Era

Point 1. SNS Design with AI

In the AI era, develop essential service planning and design capabilities for backend developers through Spring Boot and a real SNS project. Strengthen your practical competitiveness by cultivating the ability to determine what tasks to assign to AI.


Point 2. Hands-on SNS Backend Development Experience

Beyond simple examples, you'll build core features of a real SNS like Twitter (signup, login, follow, timeline, posts, etc.). Master backend design skills while learning technology stacks used in real-world projects such as Redis and PostgreSQL.


Point 3. Training in Scalable Architecture Design

You'll learn how to solve concurrency issues in various features such as likes, view counts, and follower counts, and secure scalability for timeline services through fan-out architecture. You'll study practical design principles that start small and scale progressively.


Point 4. How to Utilize AI Code Generation?

Learn how to critically review AI-generated code and design effective prompts. Develop the ability to leverage AI as your best development tool based on a deep understanding of architectural patterns.

Do backend design and the AI era feel overwhelming?
This course was created just for people like you.


✔️ Junior backend developers preparing for the AI era

  • Those who want to develop the ability to properly design and operate AI-generated code

  • Those who want to directly design and build a Twitter-like SNS backend at a real service level

  • Those who want to gain in-depth experience with core practical technology stacks such as Spring Boot, Redis, PostgreSQL, and S3

✔️ Those who have backend development experience but find it difficult to plan/design new services

  • Those who want to experience the entire process from service planning to building an actual working backend system

  • Those who want to develop the judgment to assign roles to AI and derive optimal results

  • Those who want to clearly understand various architecture patterns and the rationale behind technology choices

✔️ All developers who want to maximize development productivity using AI

  • Those who want to go beyond AI code generation tools and effectively integrate AI into actual service design

  • Those who want to implement software knowledge into actual operational systems

  • Those who want to elevate their design capabilities, data-driven thinking, and insight into technology selection to the next level



In addition to this,

1) Providing learning motivation through missions

The curriculum includes 6 missions to help students take action.
As you complete the missions, make sure to design them yourself and learn to the point where you can explain the implementation on your own.


2) Event Mission

One of the 6 missions is a 🎁event mission, and those who participate by 'writing' the mission (first-come, first-served) will receive
a 60% discount coupon for another Hanjo course, Complete a Full Cycle of Backend Service with Spring Boot and AWS
, so be sure to participate!




Stop relying solely on AI tools.
Transform into a backend design expert who commands AI.

Notes Before Enrollment


Practice Environment

  • Operating System: Windows, macOS, and Linux are all supported.

  • Development tools: IntelliJ IDEA and JDK 25 will be used.

  • Additional tools: Installation of Docker, Git, Postman (or similar API testing tools) is recommended.

Prerequisites and Notes

  • It would be helpful to have an understanding of basic Java and Spring Boot syntax.

  • Basic understanding of RDBMS (PostgreSQL, MySQL, etc.) concepts and SQL writing skills are recommended.

  • While AI is utilized, development knowledge to judge code accuracy is important.

  • An open mind toward learning new technologies and an active participatory attitude are necessary.

Learning Materials

  • Lecture slide PDF files will be provided.

  • Practice code and project source files are provided through GitHub.

  • It is important to practice reviewing and applying AI code generation results.


Recommended for
these people

Who is this course right for?

  • Students and junior developers with little backend design experience

  • For those who want to fill in their knowledge of backend server-side architecture

  • People who want to actually create a service that operates using AI

Need to know before starting?

  • Spring Boot (Introduction)

  • Java (Beginner)

Hello
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196

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9

Reviews

12

Answers

4.9

Rating

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Curriculum

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52 lectures ∙ (5hr 10min)

Course Materials:

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