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

Accounting & Finance FinTech and Financial Intelligence

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
2235-FN099A

Credit
6
Study mode
Part-time
Start Date
05 Jul 2024 (Fri)
Next intake(s)
Sep 2024
Duration
30 hours
Language
English
Course Fee
Course Fee: $9600 per programme (* course fees are subject to change without prior notice)
Deadline on 21 Jun 2024 (Fri)
Enquiries
2867 8331
2861 0278
Apply Now

Today and Upcoming Events

27
May 2024
(Mon)

Online Executive Certificate / Diploma Information Seminar - Big Data & FinTech Series (27 May 24)

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 finedec@hkuspace.hku.hk for One-on-One after-office-hour consultation, by appointment only.

Accept new applications for Jul 2024 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 2235-FN099A Apply Online Now
Apply Online Now

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

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 5 Jul 24 (Fri) 19:00-22:00
2 12 Jul 24 (Fri) 19:00-22:00
3 19 Jul 24 (Fri) 19:00-22:00
4 26 Jul 24 (Fri) 19:00-22:00
5 2 Aug 24 (Fri) 19:00-22:00
6 9 Aug 24 (Fri) 19:00-22:00
7 16 Aug 24 (Fri) 19:00-22:00
8 23 Aug 24 (Fri) 19:00-22:00
9 30 Aug 24 (Fri) 19:00-22:00
10

6 Sep 24 (Fri)

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: $9600 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 $9,600 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 AI, DeFi 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 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.

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 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.