Main content start
Change.每天多學一點 改變.可大可小

Accounting & Finance FinTech and Financial Analytics

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)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN099A
Application Code
2370-FN099A

Credit
6
Study mode
Part-time
Start Date
24 Feb 2026 (Tue)
Next intake(s)
Jul 26
Duration
30 hours
Language
English
Course Fee
Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
Deadline on 09 Feb 2026 (Mon)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

10
Dec 2025
(Wed)

How to Design a Strong-Stock Analytics Dashboard System (强勢股分析系統)? (10 Dec 2025)

To design a stock price analytics system, we need to do the following: Collect historical stock prices Transform the collected stock price record to an appropriate format for presentation Present the transformed stock price datasets in a useful layout to facilitate analytics and investors’ review.   In this talk (webinar), the speaker will showcase how to design a Strong Stock Analytics Dashboard with a BI approach. This would give you a fresh view of the practical use of data automation and data visualization techniques.   During this webinar, you will explore how a Strong Stock Analytics Dashboard will help you to: review the recent trend of HSI identify the strong stocks and weak stocks based on a specified definition of price momentum compare the ratio between the strong stocks and weak stocks according to your selected price momentum definition do sectoral analysis of the strong / weak stocks   This is an advanced application of data analytics techniques with common financial data.  You will find this webinar inspiring and will give you food for thought on how to make use of learnt data techniques for financial stock investment analysis.   Sample Screenshots below:   Related Programme Links: Certificate for Module (Technical Analysis and Data Analytics for Stock Investment) - HKU SPACE: FinTech and Financial Intelligence, Data Science courses https://hkuspace.hku.hk/prog/exe-cert-in-interpretation-and-visualization-of-business-big-data https://hkuspace.hku.hk/prog/cert-for-module-business-intelligence-and-data-automation

17
Dec 2025
(Wed)

Any correlation between Bitcoin, Ethereum and Gold? And now Stablecoin Explained (17 Dec 2025)

Bitcoin and Ethereum are the most dominant cryptocurrencies, both accumulative account for over 90% in term of market capitalization excluding stablecoin, out of more than two thousands currently in the market. They are both in a form of digital asset that trades via various DEX or centralizated regulated trading platforms. However there are quite many key differences among them though. Bitcoin (BTC) is designed as a monetary storage (some proclaim as alternative of Gold) and medium of transaction and as an alternative to fiat currency. Ethereum (ETH), otherwise, is intended for complex smart contracts or dApps which contribute and act as key infrastructure of the emerging Web3.0 future. In light of recent rapid further innovation (like staking protocol) and adoption, the price of BTC and ETH have been risen more than double in past 12 months and also exhibited a huge volatility. The speaker will give a brief introduction of above crypto with some attention drawn to the relationship and correlation among Bitcoin, Ethereum, Gold, XRP and S&P500 – as shown in below charts. The speaker will then also talk about the latest development and impacts of the recently passed GENIUS Act in U.S. and the Stablecoins Ordinance (Cap. 656) in HK. To say, Stablecoin per se. is NOT referring the price to be fixed or stable, it’s referring to link or collateralize by some tangible asse shifting from no intrinsic value issue. At 10 Oct 2025, one of most selloff in crypto, USDe has experienced flash crash to as low as 0.65 USDEUST, per shown below. Source: Bloomberg   Language: Cantonese (Supplemented with English)

Accept New Applications for Feb 2026 intake! There are practical classes in the computer laboratory. Generative AI has various applications, and decentralized finance is a popular topic. Challenges, opportunities, risks, and governance issues around Gen AI and DeFi will be discussed. Our professional lecturer will illustrate the development of a Chatbot using natural language processing techniques. Welcome to your online application!

Highlights

The programme aims to provide students with contemporary knowledge on the latest development in generative artificial intelligence (AI) and risk governance. It aims to equip students with the essential knowledge and practical skills to analyse the risks and opportunities of AI and decentralized finance (DeFi), and develop chatbots using natural language processing (NLP) techniques. The course also discusses the risk governance and ethical considerations related to AI and DeFi.
 
 

A

Programme Details

Intended Learning Outcomes (ILOs) of the Programme

 

On completion of the programme, students should be able to

  1. explain generative artificial intelligence (AI), risk and governance with AI;
  2. outline the infrastructure components of decentralized finance (DeFi);
  3. assess the opportunities and risks associated with DeFi and tokenisation;
  4. discuss the business implications of AI and risk governance; and
  5. apply computational tools to develop chatbots using natural language processing (NLP) techniques.
Application Code 2370-FN099A Apply Online Now
Apply Online Now

Days / Time
  • Tue, Thu, 7:00pm - 10:00pm
Duration
  • 30 hours per programme
Venue
  • Hong Kong Island Learning Centre
  • Kowloon East Campus
  • Kowloon West Campus

Modules

Syllabus

(1) Overview of generative artificial intelligence (AI)

  • Key inputs to AI and the current applications of AI
  • The economics of AI and its impact on different industries: competition and business implications of data harvesting
  • Data analytics and practical deployment of AI
  • Overview of generative AI and implications of human-like output
  • Creating effective prompts with generative AI
  • Limitations and economic impacts of generative AI (e.g., ChatGPT)
  • Business cases around AI and risk governance

(2) Introduction to decentralized finance (DeFi) and risk governance

  • Overview of DeFi and the key infrastructure components: cryptocurrency, smart contracts, decentralized application (dApps)
  • Issues around DeFi: inefficiency, limited access, opacity, centralised control, and lack of interoperability
  • Introduction to the transaction mechanics, tokenisation, and various types of tokens used in DeFi: fungible and non-fungible tokens (NFTs), decentralized exchanges (DEX), automated market makers (AMMs), collateralised and flash loans
  • Introduction to DeFi: risks, opportunities and challenges
  • Smart contract risk as a foundational risk for DeFi
  • Analysis of main risks: governance, information system, scaling, DEX, custodial, environmental and regulatory risks

(3) Risk and governance with AI and design of chatbots

  • Principles of risk and governance around AI
  • Ethical and governance issues related to AI and DeFi
  • Inherent bias in data based on human behaviours
  • Different responses to algorithmic bias and how to overcome them
  • AI and equitable algorithms: the importance of fairness and transparency in risk governance
  • Applications of computational tools to create chatbots with natural language processing techniques
  • Project development of chatbots: plan, implement, test, and deploy chatbots
  • Integration of chatbot on website and concerns around user interface/user experience (UI/UX)

Assessment method: One In-Class Exercise + Group Project Presentation

Award

Upon successful completion of the programme, students who have passed the final examination with attendance no less than 70% will be awarded within the HKU system through HKU SPACE “Certificate for Module (Generative Artificial Intelligence, Decentralized Finance and Risk Governance).”

Teachers

(1) Mr Willis Yung

Willis has over 10 years of experience in various areas of IT, including Fintech and Blockchain Technology, Business Continuity Management, Operational Resilience Management, Ethical Hacking, IT audit, and IT risk management.

Being a practitioner in Fintech and Information Technology, he is currently a Head of Technology and Operational Risk Management at a leading virtual bank in Hong Kong. He specializes in Blockchain security, Cybersecurity, e-banking technical and compliance assessment as well as IT governance and compliance in financial institutions. Prior to that, he served as the AVP of technology risk and cybersecurity at Bank of China International (BOCI) and Risk Assurance manager at PricewaterhouseCoopers (PwC), focusing on security advisory, technical assessment, regulatory review, threat and vulnerability assessment, designing and conducting cyber-attack simulation.

Willis has a Master’s degree in Information Systems from PolyU and a Bachelor’s degree in Business from The London School of Economics and Political Science (LSE). He is a professional member of HKIB and has professional designations, including Certified Blockchain Architect and Certified Blockchain Security Professional, Certified Ethical Hacker (CEH), Certificate of Cloud Security Knowledge (CCSKv4), ISO27001 Senior Lead Auditor and Certified Information Security Manager(CISM).

(2) Mr Thomas Lee

Mr Lee is a computer and project management professional who has worked in the information technology and data science industry for over 30 years under vendor environments including HP Inc., Dell, Fossil, Motorola network and GP Batteries. In the past ten years, Mr Lee focused on new product introduction, design for manufacturability, quality assurance & production risk management among manufacturing plants in China & Taiwan utilizing various data sciences tools and methodologies.  Mr Lee is qualified as a Microsoft Certified Trainer in delivering Microsoft training modules based on Azure technology.  He has been teaching courses related to Big Data, Cloud Computing, Machine Learning, Cyber Security and Fintech since 2020.  Mr Lee is a certified Project Management Professional, PMP from Project Management Institute PMI, US from 1998 and a Certified Scrum Master since 2018. Mr Lee holds a Master of Health Science degree in Biomedical Engineering from University of Toronto, St. George Campus, Canada.  He currently works on projects as an enabler for Inclusion and Accessibility utilizing the artificial intelligence technology. 

Class Details

Timetable

Lecture Date Time
1 24 Feb 26 (Tue)  19:00-22:00
2 26 Feb 26 (Thu) 19:00-22:00
3

3 Mar 26 (Tue)

19:00-22:00
4 5 Mar 26 (Thu) 19:00-22:00
5 10 Mar 26 (Tue) 19:00-22:00
6 12 Mar 26 (Thu) 19:00-22:00
7 17 Mar 26 (Tue) 19:00-22:00
8 19 Mar 26 (Thu) 19:00-22:00
9 24 Mar 26 (Tue) 19:00-22:00
10 26 Mar 26 (Thu) 19:00-22:00

Remarks: Tentative timetable is subject to change, and course commencement is subject to sufficient enrollment numbers.

 

 

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $9900 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree awarded by a recognised institution. Those with a business, finance, economics, mathematics, science, engineering, IT or computer science background would have an advantage. 

Applicants with other equivalent qualifications will be considered on individual merit.

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Certificate for Module (Generative Artificial Intelligence, Decentralized Finance 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)
COURSE CODE 33C15658A FEES $9,900 ENQUIRY 2867-8331
Continuing Education Fund Continuing Education Fund
This course has been included in the list of reimbursable courses under the Continuing Education Fund.

Certificate for Module (Generative Artificial Intelligence, Decentralized Finance and Risk Governance)

  • This course is recognised under the Qualifications Framework (QF Level [5])

Apply

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 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 personal information and 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 (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, new and continuing students of award-bearing programmes with available online service, they may also pay their course fees by Online WeChat Pay, Online Alipay or Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.

Notes

  • 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 Enrolment Centres and avoid making cheque payment under this circumstance.

  • 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, FPS or PPS by Internet will be reimbursed by a cheque, and fees paid by credit card will be reimbursed to the credit card account used for payment. 

  • 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.
  • HKU SPACE will not be responsible for any loss of payment, receipt, or personal information 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.