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[Spring AI in Action] Building Your Own 24/7 Code Reviewer & Auto-Grading Agent

An AI system that grades and reviews your code in 5 seconds - imagination becomes reality. This course is an all-in-one project that builds a **'GitHub PR Automatic Analysis and Grading Bot'** using Spring AI. When a student submits an assignment (Pull Request), the server detects it and AI analyzes the code changes (Diff). The grading results are then stored in the database, feedback is automatically posted as GitHub comments, and students can check their results on a dedicated dashboard. From backend to AI integration and frontend (Vaadin) - all with Java! This is the ultimate introductory guide for all developers who want to complete their own AI service from A to Z.

(4.0) 1 reviews

101 learners

Level Basic

Course period Unlimited

Java
Java
backend
backend
AI Agent
AI Agent
Spring AI
Spring AI
Java
Java
backend
backend
AI Agent
AI Agent
Spring AI
Spring AI

What you will gain after the course

  • Handling Webhooks: Building a Server to Detect GitHub Events in Real-Time

  • Spring AI Prompt Engineering: Persona Configuration and Precise JSON Output Control

  • Asynchronous Performance Optimization: Designing a Parallel Workflow for Simultaneous Grading and Review

  • Data Visualization: Implementing a Real-time Score Dashboard with Vaadin

Leave repetitive code reviews and grading to AI.

With Java alone, it detects GitHub PR(Pull Request) and AI analyzes and grades the code.
From student assignment submission to DB storage, GitHub comment feedback, and dashboard review
Through the experience of building an AI-based code review system, you'll develop practical system architecture design capabilities.

🎬 Oh, so this is what we're building!

1. 📢 Assignment Creation (Professor)

The professor writes skeleton code for a Java assignment (Calculator.java) that students need to complete and uploads it to a GitHub repository (main branch).

"Alright, this week's assignment is to complete a calculator that finds the sum of two numbers. Variable names must be clear, and there should be no unnecessary code for a perfect score!"

2. 👨‍💻 Working on the Assignment (Student)

The student brings the professor's repository to their own space (Sync Fork), creates a new branch (homework-1), and solves the problem.

"Hmm, a + bI just need to return that, right? All done! Time to submit it to the professor for review." The student creates a Pull Request (PR) to submit the assignment.

3. 🤖 AI Agent Activation (System)

The moment the student clicks the "Create PR" button (Click), the dormant Spring Boot server detects GitHub's signal (Webhook) and wakes up.

  • Step 1 (Analysis): The server extracts only the code changes (Diff) made by the student and passes them to the AI agent.

  • Step 2 (Grading): "Hmm, the functionality is correct, but the temp variable is unnecessary. The score is 90 points!" The AI grades objectively according to its pre-trained persona.

  • Step 3 (Save): The grading result (90 points) and feedback content are securely stored in the database (DB).

  • Step 4 (Feedback): At the same time, the AI leaves a comment on the student's PR. "The functionality is perfect! However, unnecessary variable declarations can waste memory."

4. 📊 Check Results (Student)

The student receives a notification just 5 seconds after submitting the PR.

"The grading is already done?"

The student accesses a dedicated dashboard (web page) and enters their GitHub ID. The screen displays the score (90 points) of the assignment they just submitted and the AI's feedback, neatly organized in tables and badges.

Spring AI in Practice is
a course where you build an AI Code Review & Grading Agent yourself.

Agentic Systems
Parallelization Workflow

Beyond simple lectures, build a production-ready AI code review system from start to finish that detects student assignment submissions, analyzes and grades code with AI, and automatically registers feedback on GitHub.

AI Automated Code Review

Strengthen your full-stack development capabilities through GitHub API integration, AI agent design, parallel workflow implementation, MySQL data storage, Vaadin-based dashboard development, and GitHub Webhooks integration.

Setting up External Access Using ngrok

AI Agent Design, Parallel Workflow Implementation

GitHub Webhook Detection

AI Auto-Grading DB Storage

Check Postman Score

Build real service development experience based on Spring AI, Spring Boot, and Java, from GitHub Webhooks, AI prompt engineering, asynchronous processing, to dashboard implementation using Vaadin.

Dashboard Implementation Using Vaadin

Break free from repetitive code reviews and grading tasks,
Upgrade your AI development skills to the next level!

Step-by-step LBD (Learning by Doing) Learning

Project Overview and AI Agent Introduction

This section introduces the overall overview of a project that creates your own 24/7 code reviewer and automatic grading agent using Spring AI. It explains the basic concepts of AI agents, how to build agents using only Spring Boot-based backend Java technology, and the necessity of code review and grading automation.

Development Environment Setup and External Integration

This section covers the essential steps for setting up the practice environment. You'll learn how to configure external access using ngrok, issue a GitHub Personal Access Token, and register GitHub Webhooks. Additionally, the integration process is verified through GitHub assignment distribution and practical simulations from both instructor and student perspectives.

Project Creation and Webhook Integration Testing

Create a Spring Boot project and perform initial environment setup. Implement a controller to receive GitHub Webhook events, and verify the integration status by testing Webhooks for 'opened' and 'synchronized' events when Pull Requests occur

Core Business Domain Design

Design and implement the domain layer for the project's core business logic. Establish the foundation for data management by defining the domain layer including Entities and DTOs, and the Repository layer for data access.

GitHub API Integration and Tool Implementation

Prepare RestClient configuration for communication with the GitHub API, and implement functionality to retrieve changed code (Diff) from Pull Requests and post review comments on Pull Requests. Develop Tools that AI agents can invoke to strengthen integration with external systems.

Implementing Spring AI-based Agents

Develop core agents using the Spring AI framework. Theoretically explain and implement ReviewAgent, which handles code reviews, and GradingAgent, which performs grading logic, to complete the AI agent operations.

Implementing Parallel Processing and Integrated Service Logic

To enhance the efficiency of AI agents, we design and implement parallel workflows. We apply asynchronous logic to process review and grading tasks simultaneously, and develop a PullRequestService that manages them in an integrated manner to complete the overall business flow.

Web Controller and Data Visualization Implementation

Implementing Web Controllers and Data Visualization Develop web controllers to expose the implemented service logic externally. Implement controllers for webhooks and grading verification, and use the Vaadin framework to provide a visualized view where students' grading results can be checked.

Project Extension and Wrap-up

Explore additional expansion possibilities for the developed AI agent and finalize the project. Provide guidance on all materials and source code used in the course, and comprehensively summarize the learning content.

The journey to create your own AI code reviewer,
This course was made for people just like you.

✔️ Java developers who want to experience AI agent development based on Spring AI

  • Those who want to build AI services in a Spring Boot environment without Python

  • Anyone who wants to build an agent that automatically analyzes and grades GitHub Pull Requests

  • Those who want to apply AI prompt engineering and tool utilization techniques to real-world projects

✔️ Job seekers who want to create a differentiated backend portfolio

  • Those who need project experience that goes beyond simple CRUD development and includes system architecture and asynchronous processing

  • Those who want to develop full-stack capabilities from AI agent development to dashboard implementation using Vaadin

  • Those who want to gain experience building GitHub integration and automation systems that can be immediately applied in real-world work

✔️ Developers and educators who want to increase productivity by automating code review and assignment grading tasks

  • Those who want to solve the burden of repetitive code reviews with AI agents

  • Those who want to design automated workflows such as saving grading results to DB and automatic feedback via GitHub comments

  • Those who want to efficiently manage grading status through a real-time dashboard based on Vaadin

Things to Note Before Enrollment

Practice Environment

  • IDE: IntelliJ IDEA Community Edition.

  • Language: Java 17 or 21.

  • Framework: Spring Boot 3.5.8 (Latest Stable).

  • Library: Spring AI 1.1.2 (or 1.1.0 Snapshot).

  • Database: MySQL8

  • AI Model: OpenAI (gpt-4o-mini or gpt-5-mini).


Prerequisites and Important Notes

  • Java web development experience is required.

  • You need to understand the basic concepts of Spring Boot.

  • If you have experience using GitHub, it will be helpful for learning.

Learning Materials

  • Learning materials are provided in Lecture 30 at the end of the video course.

  • All source code needed for the hands-on practice is provided.

  • Please refer to related materials such as GitHub Webhook, Spring AI official documentation, etc.


✏Questions & Inquiries

If there are any parts you don't understand while learning, please feel free to ask right away through the Q&A board or 1:1 open chat room

👩‍🎓Spring AI Practical (1:1 Open Chat) : https://open.kakao.com/o/sXXxSI5h

Recommended for
these people

Who is this course right for?

  • Java developers who want to adopt AI but find Python unfamiliar and want to implement AI services within the existing Spring ecosystem

  • Job seekers tired of building simple CRUD bulletin boards who need a differentiated portfolio that incorporates 'system architecture' and 'asynchronous processing'

  • Team leaders and educators who want to maximize productivity by automating repetitive code review and assignment grading tasks

  • A full-stack oriented developer who wants to quickly implement not only backend logic but also data visualization (dashboards) independently

Need to know before starting?

  • Basic knowledge of the Java programming language is required.

  • It would be good to have a basic understanding of the Spring Boot framework.

  • It would be helpful to have basic knowledge of databases and SQL.

Hello
This is bitcocom

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Hello, I am instructor Park Mae-il.
I run an SW education center and provide consulting and commissioned SW training for universities, government offices, and corporations.


📄 Major teaching experience and many others

- Goorm Specialized High School Major Camp Lectures (Full Stack Course)
- Software Meister High School Industry-Academic Cooperation Teacher
- Gwangju Artificial Intelligence Academy Lectures
- Fast Campus Backend Bootcamp Lectures
- Smart Human Resources Development Center Education Director and Lecturer
- Korea Electric Power Corporation (KEPCO) In-House Coding Entrusted Education
- Hanyang University ERICA Online Lectures
- Bit Software Education Center Operation (Overseas Employment, Government-funded Education)
- SW Recruitment Training Project (Ministry of Science, ICT and Future Planning)
- Vocational Skills Development Training Teacher for AI, IT Development, etc.
* Education Inquiries and Partnerships (KakaoTalk Channel)
* Ongoing Lectures: https://itscoding.kr

🎤 Online Educational Content Provider

Inflearn: Java, DB, MVC, Spring, Spring AI & Agent, IoT
Fast Campus: Java, Spring Boot

email : bitcocom@empas.com

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30 lectures ∙ (7hr 14min)

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