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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
2270-FN107A

Credit
6
Study mode
Part-time
Start Date
22 Feb 2025 (Sat)
Next intake(s)
Apr 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 07 Feb 2025 (Fri)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

22
Jan 2025
(Wed)

How can You Design a Dynamic Management Report to Boost your Report Productivity by 100X? (22 Jan 2025)

If you are asked to create the following Excel reports for your management: 1.      Monthly Sales Summary by Product Categories 2.      Monthly Profit Summary by Product Categories 3.      Monthly Sales Summary by Products 4.      Monthly Profit Summary by Products 5.      Monthly Customer Sales Summary 6.      Top 10 Customers by Sales Report 7.      Top 30 Products by Sales Report 8.      Top 10 Cities by Profit Report 9.      Top 5 Countries by Sales Report 10.  Top 3 Profit Summary by Product Sub-Categories How many reports will you design? Most people would develop 10 reports for their management, based on the instruction. If you want to boost your work productivity, you would think about doing it once with only one dynamic management report to cover all of the above, and even more! You may never have thought about doing this if don’t have the concept of dynamic management report design.  Here it is, a webinar for you to explore a new Excel automation that can improve your report productivity by 100X, at least. If you are interested in knowing a bit about the design, please don’t hesitate to register for the coming talk with the following link. Mr Danny Chan, the speaker, lecturer and data consultant, will present to you the solution with a live demo. Language: Cantonese (Supplemented with English) Sample Screens:

Confirmed Launch for Feb 2025 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.
 

AIMLBFA

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 2270-FN107A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 10:00am - 5:00pm
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 22 Feb 25 (Sat) 10:00-13:00 & 14:00-17:00
2 1 Mar 25 (Sat) 10:00-13:00 & 14:00-17:00
3 8 Mar 25 (Sat) 10:00-13:00 & 14:00-17:00
4 15 Mar 25 (Sat) 10:00-13:00 & 14:00-17:00
5 22 Mar 25 (Sat) 10:00-13:00 & 14:00-17:00

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.