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Accounting & Finance FinTech and Financial Intelligence

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)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN104A
Application Code
2190-FN104A

Credit
6
Study mode
Part-time
Start Date
To be advised
Next intake(s)
Aug 2024
Duration
30 hours
Language
English
Course Fee
Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
Deadline on 03 Jun 2024 (Mon)
Enquiries
2867 8331
2861 0278
Apply Now

Today and Upcoming Events

24
Jun 2024
(Mon)

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

Confirmed launch for Jun 2024 intake! There are practical classes in the computer laboratory. Introduction to generative artificial intelligence (GenAI) and its applications for business and finance will be covered. Online automation software, such as text and image generation, will be illustrated, and artificial intelligence generated content will be shared. Issues of GenAI and automation will be discussed.

Highlights

The programme aims to provide students with essential knowledge of generative artificial intelligence (GenAI) and its applications for business and finance. It equips students with technical skills to apply computational tools and online software in the computer laboratory. The programme also illustrates process automation for business and finance and discusses the issues of GenAI and automation.
 

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Programme Details

Intended Learning Outcomes (ILOs) of the Programme

On completion of the programme, students should be able to

  1. explain the principles of generative artificial intelligence (GenAI) and its technical usage;
  2. illustrate the applications of GenAI to generate content;
  3. apply computational tools and software of GenAI to perform process automation for business and finance; and
  4. discuss the issues of GenAI and automation.
Application Code 2190-FN104A Apply Online Now
Apply Online Now

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

Modules

Syllabus

(1) Introduction to generative artificial intelligence (GenAI)

  • Overview of artificial intelligence (AI) and big data development
    • Machine learning (ML) and deep learning (DL)
    • Computer vision
    • Natural language processing (NLP) and large language model (LLM)
  • Differences between analytical AI and generative AI (GenAI)
  • Principles of technologies around generative pre-trained transformers (GPT) and artificial intelligence generated content (AIGC)
    • Generative adversarial network (GAN) and Variational autoencoder (VAE)
    • Transformer-based generative model and flow-based generative model
    • GPT related tools: Open AI ChatGPT, Poe Chat, Sage, Claude, Microsoft Bing Chat, Google Bard
    • Comparison of different generations of GPT
    • Accuracy and limitations of GPT
  • Business implications of GenAI and GPT

(2) Overview of GenAI and automation tools

  • Data analytics with GenAI tools
  • Mechanism of ChatGPT: language generation, language understanding, dialogue generation, knowledge retrieval
  • Prompt and prompt engineering
  • Automation concepts using computational tools and online software
    • Overview of Microsoft Copilot
    • Overview of ChatGPT plugin
    • Overview of Chrome plugin
    • Coding and programming with GenAI tools
  • Online automation software by transforming structured data to unstructured data and vice versa
    • Summarisation tools: YouTube Summary with ChatGPT, ChatPDF
    • Presentation generation and processing tools: Tome.ai, beautiful.ai
    • Text generation and processing tools: Smodin, Jasper.ai, Copy.ai, copysmith.ai, Notion AI, Friday Chat
    • Meeting minutes recording tools: Supernormal, Tactiq
    • Image generation and processing tools: Playground AI, Midjourney, Canva, DALL·E 2, Soulgen, Fotor, Stable Diffusion, Leonardo.ai, Meta AI
    • Video generation and processing tools: Capcut, Fliki, Narakeet, Invideo, Pictory, unboring, Phenaki, Imagen Video
    • Voice generation and processing tools: MuseScore, Flat, Noteflight, Lalai.ai, Assembly AI
    • Other GenAI tools: Grammarly, Character.AI, Zapier, AIPRM for ChatGPT, Extrapolate.ai, BedtimeStory.ai, Hotoke.ai, Explainpaper, PrintIdea, RoomGPT

(3) Business and finance automated by GenAI

  • Overview of process automation for business and finance
  • Sentiment analysis for business
  • Business communication and multi-language translation
  • Financial analysis with GPT
  • Questionnaire design and business survey
  • Interview practice and business proposal design
  • Regulatory technology (RegTech) and compliance with GenAI
  • Customized learning and customized customer services for banking and finance
  • Robo advisory for finance and investment
  • Risk management by computer bot
  • Financial news generation and promotional material drafting    

(4) Issues of GenAI and automation

  • Challenges and risks around GenAI and automation
  • Plagiarism in business research and research writing
  • Data privacy and training data in AI algorithms
  • Legal and intellectual property around GenAI
  • Ethical issues around artificial intelligence generated content (AIGC)

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 a “Certificate for Module (Generative Artificial Intelligence and Automation for Finance and Business).”

Teacher

(1) Dr K.H. Cheung

King Hong is a fervent proponent of AI and ML technologies across various domains, specifically on Digital Transformation and Autonomous Data Modelling and Analytics. Possessing a strong personal network and extensive experience in consulting, King Hong has a deep understanding of integrating technology into business operations. His leadership is demonstrated in his previous consultation projects, where he led his team to research and design automated solutions for business operation workflows using cutting-edge AI and ML technologies in Computer Vision (CV) and Natural Language Processing (NLP).

During his tenure as a lecturer at two local universities in Hong Kong, King Hong enriched the learning experiences of his students using his domain knowledge, expertise, and industry experiences into a wide array of subjects. He guided master’s students in their application of Data Science techniques, including Artificial Intelligence, Machine Learning, and Data Analytics/Mining.

(2) Mr Keith Li

Keith Li is an industry veteran with 20+ years of experience in Mobile Apps, Web3, and Generative AI, is the Co-Founder and CEO of Innopage Limited. He successfully raised multiple rounds of funding from listed companies and family offices, leading innovative projects that garnered 30+ regional and international awards. Keith is a part-time lecturer at HKBU, PolyU SPEED, and CUSCS, specializing in Design Thinking, Web3, Generative AI, and Entrepreneurship. He holds a BSc in Computer Science from Kent University and an MSc in MEICOM from HKU. Currently, Keith serves as Chairman of the Hong Kong Wireless Technology Industry Association (WTIA).

(3) Mr Ken Liu

Mr. Liu, co-founder and CTO of Datatact Ltd, a startup focus on AI, Machine Learning and Big Data analytics. He is a hands on expert in his specialized area for over 10 years.  Prior to Datatact, Ken worked at Citi, HSBC, Goldman Sachs, Deutsche Bank and Credit Suisse as Algo-Trading developer. Mr. Liu earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.

(4) 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 14 Jun 24 (Fri) 19:00-22:00
2 18 Jun 24 (Tue) 19:00-22:00
3 21 Jun 24 (Fri) 19:00-22:00
4 25 Jun 24 (Tue) 19:00-22:00
5 27 Jun 24 (Thu) 19:00-22:00
6 2 Jul 24 (Tue) 19:00-22:00
7 4 Jul 24 (Thu) 19:00-22:00
8 9 Jul 24 (Tue) 19:00-22:00
9 11 Jul 24 (Thu) 19:00-22:00
10 16 Jul 24 (Tue) 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, accounting, finance, economics, mathematics, statistics, 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 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)
COURSE CODE 33C158647 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 (GenAI and Automation for Finance and Business)

  • 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.