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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Applications of GenAI and Python in Finance and Business)
證書(單元 : 生成式人工智能與Python於金融與商業的應用)

Course Code
FN183A
Application Code
2455-FN183A

Credit
6
Study mode
Part-time
Start Date
21 Nov 2026 (Sat)
Next intake(s)
Feb 2027
Duration
30 hours
Language
English
Course Fee
Course Fee: HK$10,800 per programme (* course fees are subject to change without prior notice)
Deadline on 11 Nov 2026 (Wed)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Accept New Applications for Nov 26 intake! There will be practical classes in the computer laboratory.

Highlights

The programme aims to equip students with foundational knowledge of generative artificial intelligence (GenAI) and practical Python skills tailored to finance and business. Following a logical progression from core syntax and large language model application programming interfaces (LLM APIs) to data automation, financial analytics, agentic workflows, and compliant deployment, students will learn to design, build, and deploy intelligent systems that enhance decision-making, automate complex operations, and drive innovation. The programme also cultivates students’ ability to apply GenAI tools and Python code to solve real-world financial problems while embedding ethical, governance, and regulatory awareness to deliver responsible, production-ready solutions.

Programme Details

On completion of the programme, students should be able to

  1. explain the technological elements of generative artificial intelligence (GenAI) and discuss retrieval‑augmented generation (RAG) systems, agentic workflows, and intelligent bots;
  2. apply GenAI tools and Python to automate data ingestion, cleaning, exploratory data analysis, and financial ratio extraction for business intelligence workflows;
  3. analyse financial time series, credit scoring, fraud patterns, customer segments, market baskets, GenAI‑augmented simulations; and
  4. critically evaluate the tradeoffs of deploying GenAI in finance and business, including hallucination detection, model governance, fairness audits, and regulatory compliance.
Application Code 2455-FN183A 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 GenAI and Python for Finance

  • Overview of generative artificial intelligence (GenAI) and the financial technology (FinTech) landscape
  • Introduction to GenAI tools and software
  • Basic Python syntax and Python libraries
  • Human-computer interaction (HCI) in finance and business contexts
  • Prompt engineering for beginners
  • Interacting with large language model application programming interfaces (LLM APIs) via Python
  • Foundations of LLMs and GenAI architecture, and multimodal source grounding

(2) Data wrangling and automated business intelligence

  • Financial data structures in Python
  • Automated data ingestion and mind map
  • Data cleaning and preprocessing for business intelligence
  • Exploratory data analysis (EDA), data visualisation and infographics
  • Automated key performance indicators (KPIs) dashboard creation
  • Prompt engineering for business and financial analysts
  • Automated financial ratio extraction from financial statement

(3) Financial analytics and risk modelling

  • Statistical analysis of financial time series
  • Financial forecasting and trend analysis
  • Scenario generation for value at risk (VaR) using LLM-simulated shocks
  • Portfolio optimisation and asset allocation
  • Explainable AI (XAI) for credit scoring
  • Fraud detection systems
  • Customer segmentation and churn prediction
  • Market basket analysis and promotional copy generation
  • Dynamic pricing recommendation engine

(4) GenAI automation, retrieval-augmented generation (RAG), and agentic workflows

  • Overview of GenAI and agentic AI
  • Retrieval-augmented generation (RAG) systems and NotebookLM
  • Vector databases for business search and deep research agent
  • Natural language to structured query language (SQL)
  • Automated financial report summarization, source-grounded question and answer (Q&A)
  • AI-driven sentiment analysis, podcast and video generation
  • Synthetic data generation for financial modelling
  • Contract intelligence, legal document review and in-line citations
  • Agentic workflows for multi-step analysis
  • AI agents for task automation, automated study and learning
  • Customer service automation with intelligent bots

(5) Deployment, governance, and compliance

  • Building AI web applications
  • Cloud integration for AI workflows
  • Machine learning operations (MLOps) and large language model operations (LLMOps) in finance
  • Fine-tuning LLMs on domain-specific data
  • Hallucination detection and validation layers
  • Model governance and version control for prompts
  • Fairness audits of GenAI-augmented models
  • Regulatory compliance
  • Cost-benefit analysis of GenAI APIs vs. open-source models
  • AI ethics, bias, data privacy and governance
  • The future of AI in regulatory technology (RegTech) and FinTech

Assessment method: In-class 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 (Applications of Generative Artificial Intelligence and Python in Finance and Business)".

Class Details

Timetable

Lecture

Date

Time

1

21 Nov 26 (Sat)

13:00-19:00

2

28 Nov 26 (Sat)

13:00-19:00

3

5 Dec 26 (Sat)

13:00-19:00

4

12 Dec 26 (Sat)

13:00-19:00

5

19 Dec 26 (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 (Non-refundable)

Course Fee
  • Course Fee: HK$10,800 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, Higher Diploma or Associate Degree awarded by a recognised institution where the language of teaching and assessment is English. Those with a background in business, accounting, finance, economics, mathematics, statistics, science, engineering, IT or computer science 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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