Programme outline
Learning objectives
By the end of the course, participants will learn:
- to understand the principles and applications of foundation models in the legal domain.
- to employ prompt engineering techniques to optimise the performance of Artificial Intelligence (AI) assistants.
- to utilise Large Language Models (LLMs) for tasks such as legal document summarisation, classification, and information extraction.
- to identify and implement Generative AI use cases to improve legal workflows.
- to evaluate the impact of Generative AI on legal practice and decision-making processes.
- to conduct hands-on experiments with Generative AI tools and technologies to reinforce learning.
Day 1
- Welcome and Introduction
- Basic concepts of Generative AI
- Overview of Generative AI and its impact on the legal industry
- Introduction to Foundation Models and Large Language Models (LLMs)
- Basics of prompt engineering
- How prompt engineering enhances AI performance
- Case studies: Generative AI in legal workflows
- Hands-on workshop: Building Effective Prompts
Day 2
- Advanced prompt engineering techniques
- Model tuning and prompt tuning
- Retrieval augmented generation for legal
- Practical applications: summarisation, classification, and extraction
- Building a knowledge base and Institutional database for Generative AI applications
- Hands-on workshop: Implementing Use Cases for Legal Workflow
- Integrating AI assistants into legal workflows
- Ethical considerations and compliance in AI applications
- Final discussion, feedback, course wrap-up
- In-class online assessment
Assessment
- Online assessment (MCQ) and open-ended questions
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