The course aims at equipping students with an overview of latest natural language processing (NLP) technologies that have been increasingly adopted in finance sector. The course will introduce basic concepts of NLP and the advanced developments based on machine learning, especially deep learning. The topics of word representations, sequence modeling, large language models, and conversational AI will be further explored. Based on the introduced foundation in NLP, multiple financial applications will be introduced to illustrate how NLP techniques, e.g., text mining, sentiment analysis, conversational AI and large language models, can increase productivity in various scenarios, including general financial data processing practice and specific RegTech and InsurTech use cases. Students will have ample opportunities to apply the learned techniques in hands-on implementation on course projects.
在金融領域，越來越多的產品與服務採用先進的自然語言處理（natural language processing，NLP）技術以提高生產力、優化服務質素。本科目旨在讓學生深入了解NLP基礎知識和先進技術及其金融科技應用。 本科目將介紹NLP的基本知識和理論，包括詞表征、句法結構、序列建模、語言模型和對話系統，以及基於機器學習，尤其是深度學習，的最新技術進展，包括基礎模型、大語言模型和對話式人工智能。 基於這些NLP理論基礎和技術背景，本科目將通過金融科技應用實例以展示 NLP 技術（例如文本挖掘、情感分析、對話式人工智能、大語言模型生成）在多種場景下如何提高生產力與優化服務質素，包括通用的金融數據分析方法以及特定的監管科技（RegTech）和保險科技（InsurTech）實際案例。 在本科目中，學生將有充足的機會將學到的理論與技術應用於科目項目實踐中以獲得實戰經驗。學生亦會對NLP技術的能力邊界和局限性有深入理解，從而為更好地在金融科技實踐中應用NLP技術提供基礎。
