AI+ Legal Agent™

Mastering AI in Legal Systems: Your Path to Autonomous Innovation

Beginner Self-Paced 🌐 en
AI+ Legal Agent™

Highlights

Core Concepts Covered: Legal workflows, AI technologies, Natural Language Processing (NLP), and contract review automation
Advanced Topics: Explore Generative AI, predictive analytics in case outcomes, AI-driven legal research, and compliance monitoring
Capstone Application: Design real-world legal AI agents for tasks like contract review, legal research, and compliance tracking
Level
Beginner
Modules
12
Delivery
SelfPaced

About this course

  • Core Concepts Covered: Legal workflows, AI technologies, Natural Language Processing (NLP), and contract review automation
  • Advanced Topics: Explore Generative AI, predictive analytics in case outcomes, AI-driven legal research, and compliance monitoring
  • Capstone Application: Design real-world legal AI agents for tasks like contract review, legal research, and compliance tracking
  • Career Readiness: Build expertise to thrive in AI-powered legal roles, with mentorship and hands-on training in designing legal AI agents

This course includes

📊 Beginner level 🌐 en 🎓 Self-Paced

Course curriculum

12 chapters · 44 lessons

1.1 AI Basics 1.2 What is LegalTech? 1.3 A Brief History of AI 1.4 Why AI in Law? 1.5 Emerging Trends in Legal AI Agents and the Rise of Intelligent Automation 1.6 Case Study: Revolutionizing Legal Drafting: Allen & Overy’s Integration of Harvey AI: 1.7 Case Study: AI-Powered Contract Review in a Multinational Legal Department

🔒 1.1 AI Basics
🔒 1.2 What is LegalTech?
🔒 1.3 A Brief History of AI
🔒 1.4 Why AI in Law?
🔒 1.5 Emerging Trends in Legal AI Agents and the Rise of Intelligent Automation
🔒 1.6 Case Study: Revolutionizing Legal Drafting: Allen & Overy’s Integration of Harvey AI:
🔒 1.7 Case Study: AI-Powered Contract Review in a Multinational Legal Department

2.1 AI Agents in the Legal Field 2.2 Defining Characteristics of an AI Agent 2.3 How AI Agents Differ from AI Tools 2.4 Types of AI Agents (High-Level Functional Overview) 2.5 Types of AI Agents (Design Architecture-Based) 2.6 Case Study 2.7 Tools and Libraries for AI Agent Development in LegalTech 2.8 Legal AI Agents in Trend

🔒 2.1 AI Agents in the Legal Field
🔒 2.2 Defining Characteristics of an AI Agent
🔒 2.3 How AI Agents Differ from AI Tools
🔒 2.4 Types of AI Agents (High-Level Functional Overview)
🔒 2.5 Types of AI Agents (Design Architecture-Based)
🔒 2.6 Case Study
🔒 2.7 Tools and Libraries for AI Agent Development in LegalTech
🔒 2.8 Legal AI Agents in Trend

3.1 Introduction to NLP in AI Agents 3.2 Language Models 3.3 Customizing GPT for Legal Work 3.4 The Rising Role of Prompt Engineering in Legal AI

🔒 3.1 Introduction to NLP in AI Agents
🔒 3.2 Language Models
🔒 3.3 Customizing GPT for Legal Work
🔒 3.4 The Rising Role of Prompt Engineering in Legal AI

4.1 Introduction: What Is eDiscovery and Why Automate It? 4.2 Introduction to DISCO AI (Cecilia) 4.3 Cecilia Q&A 4.4 AI-Powered Investigations with Reveal AI

🔒 4.1 Introduction: What Is eDiscovery and Why Automate It?
🔒 4.2 Introduction to DISCO AI (Cecilia)
🔒 4.3 Cecilia Q&A
🔒 4.4 AI-Powered Investigations with Reveal AI

5.1 What is Contract Review? 5.2 What Is an AI Contract Review Agent?

🔒 5.1 What is Contract Review?
🔒 5.2 What Is an AI Contract Review Agent?

6.1 What is a Legal Research Agent? 6.2 Real-World Insights — AI Lawyer in Action 6.3 AI Legal Research – Use Cases in Practice

🔒 6.1 What is a Legal Research Agent?
🔒 6.2 Real-World Insights — AI Lawyer in Action
🔒 6.3 AI Legal Research – Use Cases in Practice

7.1 Compliance and Risk Monitoring 7.2 Compliance & Risk Monitoring Agents 7.3 Hands-On Activity

🔒 7.1 Compliance and Risk Monitoring
🔒 7.2 Compliance & Risk Monitoring Agents
🔒 7.3 Hands-On Activity

8.1 Introduction to Legal Chatbots 8.2 Key Use Cases in Legal Practice 8.3 Legal Architecture & Design Principles

🔒 8.1 Introduction to Legal Chatbots
🔒 8.2 Key Use Cases in Legal Practice
🔒 8.3 Legal Architecture & Design Principles

9.1 Introduction to AI in IP Filing and Patent Drafting 9.2 Core AI Agent Functionalities 9.3 Introduction to AI Tools for Patent Drafting and Management

🔒 9.1 Introduction to AI in IP Filing and Patent Drafting
🔒 9.2 Core AI Agent Functionalities
🔒 9.3 Introduction to AI Tools for Patent Drafting and Management

10.1 Introduction to Case Outcome Prediction? 10.2 Feature Engineering in Legal Case Outcome Prediction 10.3 The Rise of Multi-Agent Legal Workflows

🔒 10.1 Introduction to Case Outcome Prediction?
🔒 10.2 Feature Engineering in Legal Case Outcome Prediction
🔒 10.3 The Rise of Multi-Agent Legal Workflows

11.1 Managing Bias in Legal AI 11.2 Legal Accountability in Autonomous Agent Deployment

🔒 11.1 Managing Bias in Legal AI
🔒 11.2 Legal Accountability in Autonomous Agent Deployment

12.1 Applying AI to Solve Real Legal Problems 12.2 Document Your Inputs and Prompts

🔒 12.1 Applying AI to Solve Real Legal Problems
🔒 12.2 Document Your Inputs and Prompts

AI Tools Used

TensorFlow TensorFlow
Power BI Power BI
Keras Keras
SQL SQL
Apache-Spark Apache-Spark
Python Python
Matplotlib Matplotlib

Prerequisites

Basic understanding of legal workflows, Interest in AI and legal innovation, No prior coding experience required, Familiarity with digital tools

Exam Details

50 questions, 70% passing, 90 minutes, online proctored exam

Mode of Learning

Delivery: SelfPaced