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Accounting & Finance FinTech and Financial Intelligence

Executive Certificate in Text Analytics and NLP with Financial Technology

Course Code
Application Code
Study mode
Start Date
10 Sep 2024 (Tue)
Next intake(s)
Dec 2024
2 months to 3 months
Course Fee
Course Fee: $9000 per programme (* course fees are subject to change without prior notice)
Deadline on 27 Aug 2024 (Tue)
2867 8331
2861 0278
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Today and Upcoming Events

Jun 2024

Online Executive Certificate / Diploma Information Seminar - Big Data & FinTech Series (24 Jun 2024)

The recent advances in Big Data and AI have major impact on the investment and trading community.  Now different types of alternative data from news, social sentiment to satellite images can be used to construct and manage investment portfolios. Moreover, Machine Learning is applied to stock price predictions while Reinforcement Learning (Alpha-Go) technique is employed into trading strategies discovery. This programme is suitable for degree holders and Executives who wish to enhance their knowledge and current market practices in the Big Data and FinTech series. Seminar topics: Course details, entry requirements, assessment requirements. This information seminar provides details about: -Executive Diploma in Financial Analytics  行政人員文憑《金融數據分析》 -Executive Certificate in Banking and Financial Technology  行政人員證書《銀行及金融科技》 -Executive Certificate in Big Data and Business Analytics  行政人員證書《大數據與業務分析》 -Executive Certificate in Big Data and Predictive Analytics  行政人員證書《大數據與預測分析》 -Executive Certificate in Big Data, A.I. and Investing  行政人員證書《大數據,人工智能與投資》 -Executive Certificate in Applications of Blockchain in Financial Technology  行政人員證書《區塊鏈在金融科技的應用》 -Executive Certificate in Applied AI and Predictive Analytics for Business  行政人員證書《應用人工智能與商業預測分析》 -Executive Certificate in AI and Deep Learning in Quantitative Finance  行政人員證書《量化投資:人工智能與深度學習》 -Executive Certificate in Applied Business Analytics and Decision Optimization  行政人員證書《應用商業分析與決策優化》 -Executive Certificate in Interpretation and Visualization of Business Big Data  行政人員證書《商業大數據視覺化及資訊演繹》 -Executive Certificate in Financial Decision Making: Big Data and Machine Learning  行政人員證書《財務決策:大數據及機器學習》 -Executive Certificate in Text Analytics and NLP with Financial Technology 行政人員證書《金融科技:文字分析與自然語言處理》 -Certificate for Module (Big Data Governance and Data Compliance)  證書(單元 : 大數據治理及數據合規) -Certificate for Module (Business Analytics and Web Scraping)  證書(單元 : 商業分析及網站擷取) -Certificate for Module (Robotic Process Automation with Business and Financial Applications)  證書(單元:機械人流程自動化於商業與財務應用) -Certificate for Module (Distributed Ledger and Blockchain with Business Applications)  證書(單元 : 分散式帳本與區塊鏈的商業應用) -Certificate for Module (Business Intelligence and Data Automation)  證書(單元 : 商業智能與數據自動化) -Certificate for Module (Business Process Automation with VBA and Python)  證書(單元:商業流程自動化 – VBA及Python) -Certificate for Module (Business Forecasting and Predictive Analytics for Financial Decision Making)  證書(單元:財務決策的商業分析與預測) -Certificate for Module (Technical Analysis and Data Analytics for Stock Investment) 證書(單元 : 股票投資的數據與技術分析) -Certificate for Module (Sustainable Finance and Green FinTech) 證書(單元 : 可持續金融與綠色金融科技) -Certificate for Module (Generative AI, DeFi and Risk Governance) 證書(單元 : 生成式人工智能、去中心化金融與風險管治) -Certificate for Module (Web 3.0 and FinTech) 證書(單元 : 第三代互聯網與金融科技) -Certificate for Module (GenAI and Automation for Finance and Business) 證書(單元 : 生成式人工智能及金融與業務自動化) -Certificate for Module (Financial Data Analytics with Python and Power BI) 證書(單元 : 金融數據分析–Python 及Power BI) -Certificate for Module (AI and ML with Business and Financial Applications) 證書(單元 : 人工智能與機器學習 - 商業與財務應用) -Certificate for Module (Financial Informatics and Data Analytics) 證書(單元 : 金融信息學與數據分析) -Certificate for Module  (Web Application Programming for Finance and Business) 證書(單元:金融與商業網頁應用編程) Unable to join us at the Information Seminar? Email to for One-on-One after-office-hour consultation, by appointment only.

Accept new applications for Sep intake! There will be practical classes in the computer laboratory. ChatGPT, a kind of Generative AI (Gen AI), is very hot, and it applies the technologies of AI and Natural Language Processing (NLP) technologies. Also, text mining and textual data wrangling are commonly used in FinTech and data analytics. Moreover, our experienced lecturer will discuss sentiment analysis and the applications of natural language processing. Welcome to your online application!


The programme aims to cover the latest applications of financial technology by using text analytics and natural language processing (NLP). It provides students with a foundation in collecting, processing, managing and analyzing textual data using computational tools. It discusses the use of NLP, text analytics and machine intelligence. The programme also offers summarization and visualization of results obtained from text analytics and NLP for applications in finance.

Programme Details

On completion of the programme, students should be able to
1. identify the main elements of text analytics and natural language processing;
2. examine techniques of text analytics and natural language processing;
3. apply machine intelligence to analyze and visualize textual data using computation tools;
4. discuss the latest applications of text analytics and natural language processing in financial technology.

Application Code 2245-EP163A Apply Online Now
Apply Online Now

Days / Time
  • Tue - Wed, 7:00pm - 10:00pm


Course Content: 

Introduction to Text Analytics and Natural Language Processing (NLP)

  • Technological overview of text analytics and NLP in finance and investment: text mining, web mining, data mining, information retrieval and NLP
  • Principles of text analytics
    • Key elements of text analytics
    • Textual data wrangling: collecting, importing, organizing and cleaning textual data
    • Text mining and text analytics: web scraping, textual corpora, text processing, tokenization, stemming and stop word removal
  • Essential of natural language processing (NLP)
    • Core elements of NLP
    • Lexical parsing, syntax parsing, semantic parsing 
    • NLP and computational linguistics


Machine Intelligence, Text Analytics, ChatGPT, and NLP in Financial Technology

  • Development of machine intelligence in financial technology: AI, Machine Learning, and Deep Learning
  • Introduction to computation tools for text analytics and NLP: R, Python, Tensorflow, Pytorch
  • Basic algorithms from deep learning: linear regressions, SVM
  • Introduction to Neural Networks for Text Analytics and NLP: Convolution Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Generative Adversarial Networks (GAN)
  • Techniques for text analytics and NLP: bag-of-words, word weighting schemes, document classification, document clustering, sentiment analysis, and model building
  • Introduction of ChatGPT and its difference with traditional text analytics
  • Generative model for large language model (LLM)

Text Analytics and NLP in Financial Decision Making

  • Real-world financial information and textual datasets
    • Financial texts from corporate disclosures, financial reports, professional periodicals, aggregated news, message boards and social media
    • Summarization of textual data and information
    • Display and visualization of results: word cloud
    • Financial intelligence from analyzed textual data
  • Applications and Issues of text analytics and NLP for financial decision making
    • Statistical and cultural bias in datasets
    • Financial slang and NLP for sentiment analysis
    • Analysis of financial textual data
    • NLP and deep learning for predicting stock price movements
    • Semantic model building for financial forecasting
    • Credit risk analysis using text analytics
    • Implications and limitations of text analytics and NLP in making finance and investment decision
    • Improving financial services with NLP

Assessment method:  Two assignments exercise + group presentation


The Executive Certificate will be conferred to candidates who have attained PASS grade and achieved at least 70% attendance of the programme.


(1) Ms Rowena Lai
Ms. Lai has extensive experience in business and data analytics in different business sectors. She is currently working in a well-known international bank and leading various data analytics projects. She graduated from the Chinese University of Hong Kong with a Bachelor of Science degree (major in Mathematics and Minor in Economics), and obtained a Master of Science in International Shipping and Transport Logistics as well as a Master of Science degree in Global Supply Chain Management from the Hong Kong Polytechnic University. Ms. Lai is currently a Certified Analytics Professional (CAP) from INFORMS. With her practical experience in data analytics and professional knowledge in financial technology, she teaches "Big Data and FinTech" module under Postgraduate Diploma in Investment Management and Financial Intelligence, Executive Certificate in Big Data and Data Analytics as well as Executive Certificate in Text Analytics and NLP with Financial Technology.
(2) Mr Clive Yip
Mr. Yip is a practitioner in Data Analytics.  He has 10 years of experience in both Big 4 consulting firms and multinational companies.  He is currently working as a Senior Data Analytics Consultant in a leading insurance company, using Python, SQL and other Big Data technologies to analyse and monitor any non-compliance or fraudulent activities.  He has a Master’s degree in Information Technology from HKUST and a Bachelor’s degree from the University of Southern California.  Before entering the data analytics field, he worked as a financial auditor in Ernst and Young and is a Certified Public Accountant (CPA) in Hong Kong and Canada. 

(3) Professor Daniel Chan

Professor Chan is a veteran IT management consultant having held CTO, ED, INED, GM and Director positions in MNC’s with 20+ years of experience.  Currently, he runs a couple of AI companies in the space of data annotation and pose detection on top of his advisory role to other AI companies working in different spaces.  His largest text analytics project involves 60M text documents which calls for the latest technologies available in Natural Language Processing (NLP).  He is also the course leader for “Machine Learning for Financial Data” in an MSc FinTech programme in a university in Hong Kong.  

(4) Dr Cheung King Hong

Dr Cheung has a deep interest in applying data technologies in different functions and domains to enhance the quality of human life and environment.  He has deep understanding and insight about the use and integration of technologies in business through his personal network, past experiences on consultancy as well as rich experiences in lecturing a wide range of subjects during his career as a teaching staff member in one of the universities in Hong Kong.  He has leaded and guided master students to apply Data Sciences techniques, including Artificial Intelligence, Machine Learning, Data Analytics/Mining in research on medical operations and metal fracture detection in Hong Kong.

Class Details


Sep 2024 intake 

Lecture Date Time
1 10 Sep 24 (Tue) 19:00-22:00
2 11 Sep 24 (Wed) 19:00-22:00
3 24 Sep 24 (Tue) 19:00-22:00
4 25 Sep 24 (Wed) 19:00-22:00
5 2 Oct 24 (Wed) 19:00-22:00
6 8 Oct 24 (Tue) 19:00-22:00
7 9 Oct 24 (Wed) 19:00-22:00
8 15 Oct 24 (Tue) 19:00-22:00
9 16 Oct 24 (Wed) 19:00-22:00
10 22 Oct 24 (Tue) 19:00-22:00

Remarks :
-Tentative timetable is subject to change, and course commencement is subject to sufficient enrollment numbers.
-For your safety and health, please note that the School may substitute face-to-face classes with online teaching if necessary.


Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $9000 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants shall hold:
1.  a bachelor’s degree awarded by a recognized University or equivalent; or
2.  an Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant work experience.

Applicants with qualifications in quantitative areas (e.g., mathematics, engineering, statistics, computer science, information technology, economics, finance) are preferred. Those with other qualifications and substantial senior level work experience will be considered on individual merit.


Online Application Apply Now

Application Form Download Application Form

Enrolment Method
Payment Method
1. Cash, EPS, WeChat Pay Or Alipay

Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.

2. Cheque Or Bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and the applicant’s name.. You may either:

  • bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
  • or mail the above documents to any of the HKU SPACE Enrolment Centres, specifying  “Course Application” on the envelope.  HKU SPACE will not be responsible for any loss of payment sent by mail.
3. VISA/Mastercard

Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.

4. Online Payment

Online application / enrolment is offered for most open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, continuing students of award-bearing programmes, if their programmes offer online service, may also pay their course fees by Online WeChat Pay, Online Alipay and Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.


  • If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolement Centres and avoid making cheque payment under this circustance.
  • Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, WeChat Pay, Alipay, cheque or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder's credit card account.
  • In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
  • Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
  • Receipts will be issued for fees paid but HKU SPACE will not be repsonsible for any loss of receipt sent by mail.
  • For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to "HKU SPACE" to any of our enrolment centres.