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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Sovereign AI and Investment Analysis)
證書(單元:主權人工智能與投資分析)

Course Code
FN188A
Application Code
2465-FN188A
Credit
6
Study mode
Part-time
Start Date
16 Jan 2027 (Sat)
Next intake(s)
Apr 2027
Duration
30 hours
Language
English
Course Fee
Course Fee: HK$11,100 per programme (* course fees are subject to change without prior notice)
Deadline on 06 Jan 2027 (Wed)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Accept New Applications for Jan 27 intake! There will be practical classes in the computer laboratory.

Highlights

The programme aims to equip students with core knowledge of the sovereign artificial intelligence (AI), technology stack (Tech stack), capital markets, and infrastructure finance. Moving from semiconductor geopolitics and sovereign wealth fund allocations to graphics processing unit (GPU)-as-an-asset valuation and capital expenditure return on investment (CapEx ROI) estimation, students will learn to model high-capital technology infrastructure and construct resilient investment portfolios. The programme also develop students’ practical skills in navigating selective corporate sovereignty, algorithmic auditing, and supply chain de-risking, preparing students to analyse complex geopolitical and regulatory issues, risk management and public policy.

Programme Details

On completion of the programme, students should be able to

  1. analyse the geopolitical, regulatory, and financial dynamics shaping sovereign artificial intelligence (AI) and technology stack (Tech stack);
  2. critically evaluate high-capital technology infrastructure investments by applying financial modelling techniques;
  3. formulate corporate and sovereign strategies to navigate selective sovereignty tiering, vendor lock-in, and algorithmic compliance within hybrid cloud environments; and
  4. assess global risks and public policy implications, as well as perform risk-adjusted investment analysis.
Application Code 2465-FN188A 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) Foundations of sovereign artificial intelligence (AI) and technology stack (Tech stack)

  • Defining the sovereign AI, Tech stack and core pillars of the AI ecosystem
  • Introduction to generative AI (GenAI) and computational tools
  • Corporate dominance and infrastructural sovereignty and the edges of modern semiconductor manufacturing
    • The edge (I): Corporate dominance on mature semiconductor technologies and advanced silicon fabrication
    • The edge (II): Global monopoly on extreme ultraviolet (EUV) lithography machines
  • Compute infrastructure and hyperscale real estate
  • Data residency, localisation, and sovereignty
  • Open-source models vs. proprietary monopolies

(2) Infrastructure finance and capital markets

  • The AI electricity and data center capacity bottleneck
  • Project finance in sovereign AI
  • Private credit and securitisation in technology infrastructure (Tech infrastructure)
  • Public-private partnerships (PPPs) in Tech infrastructure
  • Sovereign AI finance and the three-stage capital model

(3) Sovereign wealth funds (SWFs) and geopolitical allocations

  • SWF investment mandates in AI
  • National compute programmes
  • Geopolitical risk and capital flight
  • Resource-rich vs. capital-constrained sovereign strategies
  • Survival alliances among middle powers in Europe, India, and the United Arab Emirates
  • Currency sovereignty and token economics (tokenomics)

(4) Corporate strategy and selective sovereignty

  • Core factors and value considered by sovereign AI investors
  • The economics of hybrid and sovereign clouds
  • Vendor lock-in and portability economics
  • Selective sovereignty tiering
  • Algorithmic auditing and compliance costs
  • Cultural and linguistic model tailoring

(5) Investment analysis and valuation techniques

  • Valuing semiconductor and hardware equities
  • Overview of graphics processing unit (GPU) and tensor processing unit (TPU)
  • A scarce asset class: GPU-as-an-asset valuation
  • Intellectual property (IP) valuation in the GenAI era
  • Estimating AI capital expenditure return on investment (CapEx ROI): infrastructure ROI and enterprise AI ROI
  • Green premium in AI investing

(6) Risk management and public policy

  • Deeper intervention by governments in the supply chains of advanced chip and AI companies
  • Risk-adjusted measurement to account for nations becoming exclusively dependent on foreign AI systems
  • Sovereign AI market mapping, export controls and geopolitical measures
  • Kill-switch risk, supply chain de-risking and resilience modelling
  • Ethical investing and sovereign AI alignment
  • The sovereignty trilemma

Assessment method: Individual Exercise + Group Project Presentation

 

Award

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

Class Details

Timetable

Lecture

Date

Time

1

16 Jan 27 (Sat)

13:00-19:00

2

23 Jan 27 (Sat)

13:00-19:00

3

30 Jan 27 (Sat)

13:00-19:00

4

13 Feb 27 (Sat)

13:00-19:00

5

20  Feb 27 (Sat)

13:00-19:00

Teacher Information

Mr Ivan Law

Background

Mr Ivan Law brings over two decades of combined experience in education, applied data science, and the finance industry, with a proven track record of empowering learners to master in-demand technical skills. Holding a BEng in Computer Science from HKUST and an MSc in Financial Management from the University of London, Ivan leverages his interdisciplinary background to make complex data science concepts accessible to students from diverse academic and professional backgrounds. As a part-time lecturer at CityU SCOPE, he has delivered over 2,100 instructional hours across 8 cohorts of adult learners, specializing in Python, Pandas, NumPy, data visualization (Matplotlib/Seaborn/Plotly), and AI/ML foundations. Rooted in rigorous project-based learning, his teaching philosophy prioritizes clarity, practical application, and active engagement. He designs interactive exercises and real-world projects to help learners translate theoretical concepts into actionable skills that meet workplace needs. Complementing his teaching practice is 18+ years of experience in senior roles across the banking and hedge fund industry, where he led teams in operations, risk management, and compliance at both local and US-based hedge fund firms. Serving as Director, Ivan now designs and delivers professional data science training and deploys AI/ML pipelines for SMEs. This hands-on, up-to-date experience building industry-ready solutions ensures his teaching curricula remain current with the latest tools and market demands, which further strengthens his ability to connect analytical rigor with business insights.

Fee

Application Fee

HK$150

Course Fee
  • Course Fee: HK$11,100 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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