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Accounting & Finance FinTech and Financial Analytics

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)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN107A
Application Code
2260-FN107A

Credit
6
Study mode
Part-time
Start Date
05 Dec 2024 (Thu)
Next intake(s)
Feb 2025
Duration
1 month to 2 months
Language
English
Course Fee
Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
Deadline on 21 Nov 2024 (Thu)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

02
Dec 2024
(Mon)

Web3 and Blockchain - Session IX (2 Dec 2024)

Join us for an exhilarating online talk show titled "Web3 and Blockchain IX". This session is designed to take you on a journey through the transformative landscape of blockchain technology, which is at the heart of a decentralized digital ecosystem—a significant leap from the interactive platforms of Web2. Bitcoin ETF Approval by the SEC: The crypto community is abuzz with the news that the U.S. Securities and Exchange Commission (SEC) has given the green light to a Bitcoin ETF. This approval is expected to drive significant institutional investment into the cryptocurrency market, potentially boosting Bitcoin's price and bringing it further into the financial mainstream. Hong Kong's Push for Virtual Asset Regulations: In a recent move, Hong Kong has unveiled a comprehensive regulatory framework for virtual assets, aiming to bolster investor protection and foster innovation. The new guidelines provide clear rules for cryptocurrency exchanges and digital asset service providers, signaling Hong Kong's commitment to becoming a leading hub for blockchain and fintech development. China's Digital Yuan Gains Traction: China's central bank digital currency, the digital yuan, is gaining significant traction as more businesses and consumers adopt it for everyday transactions. This development is seen as a major step towards mainstream acceptance of digital currencies and is influencing global financial systems to consider their own digital currency initiatives. Hong Kong Steps Boldly into the Cryptocurrency Spotlight: In an exciting development, Hong Kong has given initial approval to its first bitcoin and ether spot ETFs. This pioneering move paves the way for a broader acceptance of cryptocurrencies within the region’s mainstream financial systems, underscoring a significant shift towards more regulated and accessible digital asset investments. Bitcoin Halving Event: The crypto community is abuzz as the Bitcoin halving is done; this is a critical event that historically triggers a surge in Bitcoin's price by reducing the reward for mining new blocks by half. This anticipated change is stirring discussions about potential impacts on market dynamics and investment strategies. Innovative Regulatory Sandbox by HKMA: In a stride towards fostering innovation while ensuring security, the Hong Kong Monetary Authority (HKMA) is set to introduce a "sandbox" for entities interested in issuing stablecoins. This initiative will allow participants to test their business models and risk management systems under manageable conditions, enhancing investor protection and promoting responsible business practices in the digital currency sphere. Join Our Captivating Session to delve deeper into the essence of Web3 and blockchain technologies with us. Discover how these advancements are reshaping the internet and what they mean for the future of finance, privacy, and online interaction. This is more than just a talk – it's an opportunity to be part of the next digital revolution. Register now and be part of this transformative journey into Web 3.0. Language: Cantonese (Supplemented with English)  

Confirmed launch for Dec 2024 intake! There are practical classes in the computer laboratory.

Highlights

The programme aims to provide students with essential knowledge of artificial intelligence (AI) and machine learning (ML) and their applications in business and finance. It covers the practical applications of AI and ML algorithms. It equips students with computer programming skills by applying computational tools and online software. The programme illustrates various applications of AI and ML in business and finance.
 

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Programme Details

On completion of the programme, students should be able to

  1. explain the principles of artificial intelligence (AI) and machine learning (ML);
  2. illustrate the usages of AI and ML algorithms in business;
  3. apply computational tools and online software to implement AI algorithms and perform business analytics; and
  4. discuss the applications of AI and ML in business and finance.

 

Application Code 2260-FN107A Apply Online Now
Apply Online Now

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

Modules

Syllabus

(1) Introduction to artificial intelligence (AI)

  • Development of AI and key market players
  • Technological elements around AI and data science
  • Machine intelligence and human-computer interaction (HCI)
  • Analytical AI and business analytics
  • Introduction to GenAI tools and prompt engineering
  • Challenges and opportunities around artificial general intelligence (AGI) in business and finance
  • AI risks and ethics

 

(2) AI and ML algorithms powered by Python

  • Python programming
  • Python library and AI and ML algorithms
  • ML theory and methods: supervised learning algorithms, unsupervised learning algorithms, and reinforcement learning algorithms
  • Neural networks and deep learning: artificial neural networks (ANN), convolutional neural networks (CNN), recurrent neural networks (RNN), long short-term memory (LSTM), generative adversarial networks (GAN)
  • Natural language processing (NLP), large language models (LLM) and generative pre-trained transformer (GPT)
  • Computer vision and automation
  • AI and ML with practical business cases
  • AI and business analytics with Python  

 

(3) Applications of AI and ML in business and finance

  • Financial transaction analysis and fraud detection
  • Risk assessment for financial investments and loan applications
  • Stock market prediction
  • Customer segmentation and analysis
  • Credit scoring
  • Algorithmic trading
  • Sentiment analysis
  • Chatbots and virtual assistants
  • Loan default prediction
  • Customer churn prediction
  • Business process automation
  • Operational optimisation

 

Assessment method: One individual assignment  + Group Project Presentation

Award

Upon successful completion of the programme, students who have passed the assessments with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a “Certificate for Module (Artificial Intelligence and Machine Learning with Business and Financial Applications).”

 

Teacher:  

1.  Mr Alan Cheung

Mr. Alan Cheung, PRM, CQF has solid experience in quantitative finance spanning statistical analysis, derivative pricing and mathematical modeling. He has solid experience in fintech in top tier investment banks, versed in architecting low latency, high frequency algorithmic trading systems. Alan has a Master of Science in Mathematical and Computational Finance from the University of Oxford after graduating with First Class Honours in Mathematics with Statistics for Finance from Imperial College London. 

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 Dec 24 (Thu) 19:00-22:00
2 10 Dec 24 (Tue) 19:00-22:00
3 12 Dec 24 (Thu) 19:00-22:00
4 17 Dec 24 (Tue) 19:00-22:00
5 19 Dec 24 (Thu) 19:00-22:00
6 2 Jan 25 (Thu) 19:00-22:00
7 7 Jan 25 (Tue) 19:00-22:00
8 9 Jan 25 (Thu) 19:00-22:00
9 14 Jan 25 (Tue) 19:00-22:00
10 16 Jan 25 (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, 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 (ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING 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)
COURSE CODE 33C159015 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 (Artificial Intelligence and Machine Learning with Business and Financial Applications)

  • 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.