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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (FinTech and AI)
證書(單元 : 金融科技與人工智能)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN120A
Application Code
2360-FN120A

Credit
6
Study mode
Part-time
Start Date
20 Dec 2025 (Sat)
Next intake(s)
Feb 2026
Duration
30 hours
Language
English
Course Fee
Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
Deadline on 08 Dec 2025 (Mon)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

Accept New Applications for Oct 25 intake! There will be practical classes in the computer laboratory.  Discuss the concepts and applications of data analytics, machine learning, deep learning, reinforcement learning, cloud computing, Web 3.0, cybersecurity, network security, ethical hacking and RegTech. Apart from the applications of AI, topics related to GenAI and prompt engineering, natural language processing, large language models and small language models will be covered. Practical applications of FinTech and AI will be shared. 

Highlights

The programme is designed to impart contemporary knowledge in financial technology (FinTech) and artificial intelligence (AI) to students. It will equip them with critical skills to effectively utilise computational tools and online software for writing computer programmes, designing and implementing applications. Additionally, the programme demonstrates the practical applications of FinTech and AI, while addressing pertinent issues in the commercial world.

Programme Details

On completion of the programme, students should be able to

  1. explain the technological elements and design around financial technology (FinTech) and artificial intelligence (AI);
  2. use computational tools and software to develop applications;  
  3. illustrate practical applications of FinTech and AI for finance and business; and
  4. discuss the challenges and opportunities of FinTech and AI for the commercial world.
Application Code 2360-FN120A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 1:00pm - 7:00pm
Duration
  • 30 hours per programme
Venue
  • Hong Kong Island Learning Centre
  • Kowloon West Campus
  • Kowloon East Campus

Modules

Course Content :

(1) Overview of financial technology (FinTech) and artificial intelligence (AI)

  • Basic terminology related to FinTech and AI: big data, machine learning (ML), deep learning (DL), reinforcement learning (RL), cloud computing, blockchain, smart contract
  • Contemporary development of Artificial intelligence (AI): analytical AI and generative AI (GenAI)
  • Future trends and innovations in FinTech and Web3.0
  • Basic Python programming for FinTech and AI
  • Elements of text analytics: natural language processing (NLP), large language models (LLMs) and small language models (SLMs)
  • Introduction to computational tools and GenAI software
  • GenAI and prompts: prompt engineering and artificial intelligence generated content (AIGC)
  • Issues related to AI and AI ethics
  • System design with FinTech and AI
  • FinTech and network security
  • Introduction to security software and tools

 

(2) FinTech and AI applications for business and finance

  • Sustainable finance innovations and green FinTech applications
  • AI-driven financial products
  • Financial advisory powered by GenAI
  • Business automation powered by AI and FinTech
  • Customer experience enhancement through AI-powered FinTech solutions
  • Strategic implementation of GenAI for business and financial services sectors
  • AI and risk management
  • Real-time data analytics and predictive modeling for financial decision-making
  • Managerial issues around data privacy and security
  • Cybersecurity management in FinTech, cyberattacks, and defense
  • Business continuity plan and ethical hacking
  • Regulatory technology (RegTech): regulatory and compliance issues
  • AI deepfake, economic crime mitigation and financial security
  • Machine learning, fraud detection and prevention strategies in FinTech

Assessment method: 3-hour in-class exercise + Group Project Presentation

Award

Upon successful completion of the programme, students who have passed the continuous assessment and final assessment with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a "Certificate for Module (Financial Technology and Artificial Intelligence)".

 

Class Details

Timetable

Lecture Date Time
1 20 Dec 25 (Sat) 13:00-19:00
2 3 Jan 26 (Sat) 13:00-19:00
3 10 Jan 26 (Sat) 13:00-19:00
4 17 Jan 26 (Sat) 13:00-19:00
5 24 Jan 26 (Sat) 13:00-19:00

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

Teacher Information

Mr Joe Lam

Background

Joe Lam is a seasoned professional with over 20 years of expertise in the global FICC markets, known for his innovation, leadership, and strategic vision. A graduate of City University of Hong Kong with a BBA in Finance and MSc in Financial Engineering, Joe has consistently excelled in pushing financial boundaries.

Starting at Standard Chartered Bank, he honed his skills in Institutional Rates and FX, advancing through roles at institutions like Bank of Tokyo Mitsubishi UFJ, Commonwealth Bank of Australia, and Credit Suisse, where he specialized in interest rates, FX, and macroeconomic strategy. At BOCOM International and CEB International, Joe spearheaded transformative projects like Bond Connect and Equity Margin Financing.

As a Green Finance Advisor for Friends of the Earth HK, Joe champions sustainable finance, blending profitability with environmental responsibility. His commitment to knowledge-sharing continues as a member of The Polytechnic University of Hong Kong’s DBA program.

A pioneer in blockchain and cryptocurrency since 2016, Joe combines hands-on trading experience with a deep understanding of DeFi security challenges. His career embodies a lifelong dedication to learning, innovation, and shaping the future of finance.

Mr Samson Wai

Background

Samson Wai hails from the vibrant city of Hong Kong. He pursued his higher education at McGill University, where he obtained a Bachelor of Engineering in Electrical Engineering, and later at University of Michigan-Dearborn (in collaboration with HKU SPACE), where he earned a Master of Science in Finance.

Samson's career began in the technology sector and eventually stepped into the financial sector, where he quickly rose to the position of Chief Technology Officer in an asset management company. His extensive experience and innovative mindset led him to establish his own FinTech company, Wai's Consulting Services Limited, where he currently serves as the founder.

Beyond his professional achievements, Samson has a deep passion for coffee, which fuels his creativity and productivity. He is dedicated to leveraging technology to improve the lives of people, a goal that drives his work and inspires his team.

Samson's vision is to harness the power of technology to create solutions that make a meaningful impact on society. His journey from a tech-savvy engineer to a visionary leader in the consulting industry is a testament to his commitment to innovation and excellence. Samson believes in the transformative potential of technology and strives to make a positive difference in the world through his work.

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 (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.

 

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

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Certificate for Module (Financial Technology and Artificial Intelligence)
證書(單元 : 金融科技與人工智能)
COURSE CODE 33C162059 FEES $9,900 ENQUIRY 2867-8424
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 (Financial Technology and Artificial Intelligence)

  • 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.
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