This course is to introduce the techniques used to effect information extraction. Using Python, this course guides how to access web data, pre-process data, implement natural language processing and perform textual analysis. The applications to Fintech are discussed and demonstrated.

Course is delivered over 4 weeks, comprising of 20 hours of lectures and 4 hours of seminars.

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ILO being assessed

The aim of this course is to introduce students to the issues, methods and techniques of information extraction in the domain of FinTech. It will enable students to write and apply Python codes to access web data and provide students with information about issues including news scraping, social media application programming interface, users/investors opinions mining, and government open data, with different techniques employed on these issues. Through these, it will enable students to develop critical skills in retrieving information from massive online data sets and extracting the valuable parts for FinTech applications.

By the end of this course students will be able to:

1. Analyse the impact of information retrieval techniques on financial technologies

2. Analyse information complexities and natural language processing

3. Implement Python packages on retrieval and analytical tasks

4. Analyse the information content and value for FinTech applications

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.