Prompt Patterns for Developers
arigaram
We introduce basic prompt patterns for coding and advanced API prompt patterns for leveraging artificial intelligence.
Basic
prompt engineering
We explore how to create an AI judge by combining knowledge graphs, reasoning systems, and various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology.
11 learners are taking this course
Level Intermediate
Course period Unlimited
Multi-agent system
Knowledge Graph
Prolog-based inference and logical judgment
The course is currently being finalized. Please be aware that it may take some time until the course is fully completed (although updates will be made frequently). Please take this into consideration when making your purchase decision.
March 15, 2026
The list of example documents and example code has been deleted to prepare for the posting of the 2nd edition lectures. After all the 2nd edition class videos and materials are posted in the future, the documents and example codes will be organized and posted separately.
January 20, 2026
I have added more sections, along with lists of example documents and example codes for each section.
September 18, 2025
I have added the precautions to the detailed introduction page.
August 22, 2025
The detailed curriculum for the sections making up the advanced course has been changed to private. They will be made public for each section as they are completed in the future.
As AI technology advances, automation and AI judges are becoming a reality in the legal field. In this course, you will learn how to configure a multi-AI agent system using CrewAI and build an AI judge system by combining knowledge graphs with reasoning systems.
By taking this course, you will learn the fundamental concepts required to design a collaborative AI Agent system using LLM and CrewAI, analyze legal data, and directly implement an AI judge system that automatically delivers rulings.
✔ Learn how to build a multi-agent collaboration system using CrewAI
✔ Learn how to structure and utilize legal data as a knowledge graph
✔ Learn how to design rule-based and LLM-based legal reasoning systems
✔ Learn how to implement an AI judge system
Introduction to Course Overview and Learning Objectives
Establishing the basic concepts of Legal AI
Setting up the development environment and essential tools
CrewAI Architecture and Operating Principles
Designing Law-Specific Agents
Collaboration and communication between multi-agents
Concepts of Knowledge Graphs for Legal Data
Building and Visualizing Relationship Graphs
Integrating CrewAI and Knowledge Graphs
Reasoning methods for correct judgments
Deterministic Reasoning Using Prolog
Implementation of LLM-based Probabilistic Reasoning Systems
From requirements analysis to architecture design
Data Modeling and Inference Engine Design
Establishing system implementation strategies using CrewAI
Developers and legal professionals interested in the convergence of artificial intelligence and law
Planners and researchers who want to design AI legal systems applicable to practical work
Learners who want to comprehensively understand multi-agent systems, knowledge graphs, and reasoning systems.
Systematically understand the operating principles and design techniques of AI judge systems
Acquire the ability to configure legal AI that can be utilized in actual development environments
Strengthening practical skills required for future AI legal technology research and projects
Python IDE and Prolog IDE are required.
A brief introduction to the installation method will be provided during the lecture.
Format of provided learning materials: Lecture notes provided in PDF format
It is recommended to first acquire basic knowledge of the Python language and LLMs.
The code presented here is not complete and is merely a snippet for explaining concepts, so you may need to complete the code yourself.
This lecture goes beyond simple theoretical explanations and provides realistic and in-depth guidance for anyone looking to implement an actual legal AI system. Enroll now!
Who is this course right for?
Those who want to implement multi-agent systems
Those who want to create specialized AI application services
Need to know before starting?
Understanding Large Language Models (LLMs)
691
Learners
38
Reviews
2
Answers
4.6
Rating
18
Courses
I am someone for whom IT is both a hobby and a profession.
I have a diverse background in writing, translation, consulting, development, and lecturing.
All
248 lectures ∙ (29hr 32min)
Course Materials:
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