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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Agentic AI for FinTech and Business Applications)
證書(單元 : 代理型人工智能於金融科技與商業的應用)

Course Code
FN143A
Application Code
2335-FN143A
Credit
6
Study mode
Part-time
Start Date
22 Jul 2025 (Tue)
Next intake(s)
Sep 2025
Duration
30 hours
Language
English
Course Fee
Course Fee: $10,200 per programme (* course fees are subject to change without prior notice)
Deadline on 14 Jul 2025 (Mon)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Accept new applications for Jul 25 intake! There will be practical classes in the computer laboratory.

Highlights

The programme aims to provide students with contemporary developments in artificial intelligence (AI) and financial technology (FinTech), as well as an understanding of agentic AI. It equips students with practical skills to use computational tools and software to apply agentic AI in finance and business contexts. The programme also illustrates the practical applications of agentic AI to automate business workflow and processes, as well as discussing FinTech and business applications powered by agentic AI.

Programme Details

On completion of the programme, students should be able to

  1. examine the latest elements of artificial intelligence (AI) and financial technology (FinTech);
  2. assess business processes and optimise operational workflow;
  3. apply AI agents to automate financial and business operations; and
  4. illustrate the use of agentic AI for FinTech and business applications.
Application Code 2335-FN143A 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 West Campus
  • Kowloon East Campus

Modules

Course Content :

(1) Principles of Agentic Artificial Intelligence (AI) for Financial Technology (FinTech) and Business

  • Overview of the latest developments in AI and FinTech
  • Technological building blocks of AI and FinTech
  • Basics of AI algorithms and learning methodologies: machine learning, supervised learning, unsupervised learning, natural language processing (NLP), deep learning and reinforcement learning
  • Essentials of generative AI, large language models (LLMs) and small language models (SLMs)
  • Comparison between agentic AI and traditional AI
  • Human-computer interaction and autonomous operations
  • Common types of AI agents and interaction among multiple agents
  • Risks and ethics of AI
  • Agentic AI, FinTech and digital transformation for banking and finance
  • Benefits of agentic AI for finance and business

(2) Introduction to agentic AI and computational tools

  • Python programming fundamentals
  • Overview of web scraping and application programming interfaces (APIs)
  • Generative AI tools and software for finance and business
  • Chaining capabilities and AI agents
  • Agentic AI and automation tools for finance and business

(3) FinTech and business applications powered by agentic AI

  • Overview of project design, execution and workflow optimisation with AI agents
  • Business process automation and agentic AI
  • Web scraping and financial data analytics
  • Sentiment analysis and business intelligence
  • Dashboard design and reporting automation for finance and business
  • Automated investment decision making
  • Optimisation of trading strategies
  • Corporate compliance and statutory reporting
  • Regulatory Technology (RegTech) and agentic AI
  • Fraud detection and real-time analysis of transaction data
  • Personalised financial advice powered by agentic AI
  • Automated reconciliation and financial reporting
  • Customer services and AI agents

Assessment method: In-class Exercise + 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 (Agentic Artificial Intelligence for Financial Technology and Business Applications)".

 

Class Details

Timetable

Lecture Date Time
1 22 Jul 25 (Tue) 19:00-22:00
2 24 Jul 25 (Thu) 19:00-22:00
3 5 Aug 25 (Tue) 19:00-22:00
4 7 Aug 25 (Thu) 19:00-22:00
5 12 Aug 25 (Tue) 19:00-22:00
6 14 Aug 25 (Thu) 19:00-22:00
7 19 Aug 25 (Tue) 19:00-22:00
8 21Aug 25 (Thu) 19:00-22:00
9 26 Aug 25 (Tue) 19:00-22:00
10 28 Aug 25 (Tue) 19:00-22:00

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

Teacher Information

Mr. William Kin

Background

Mr William Kin is a seasoned Business Analytics, Data Science, Engineering, and Governance professional with over a decade of experience in driving data-driven decision-making and ensuring robust data governance across diverse industries. With expertise in data strategy, advanced analytics, and compliance frameworks, William has a proven ability to design and implement BI tools, machine learning platforms, and data quality standards that align with organizational goals. His experience spans roles at leading organizations in property development, financial services, supply chain, and logistics, where he has successfully led digital transformation initiatives, optimized data processes, and ensured compliance with global data regulations. Equipped with technical proficiency in tools like Power BI, Python, SQL, and cloud platforms, William is a strategic thinker and leader who transforms data into actionable insights, empowering businesses to achieve growth, innovation, and operational excellence. His multidisciplinary expertise makes him a valuable asset in bridging the gap between data science, engineering, and governance to deliver measurable business outcomes.

Fee

Application Fee

HK$150

Course Fee
  • Course Fee: $10,200 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 where the language of teaching and assessment is English. 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.

**Please upload copy of HKID and proof of degree while applying online

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.
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