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Accounting & Finance FinTech and Financial Intelligence

Executive Certificate in Applied AI and Predictive Analytics for Business

Course Code
Application Code
Study mode
Start Date
28 Oct 2023 (Sat)
Next intake(s)
Jan 2024
1 month to 2 months
Course Fee
Course Fee: $8800 per programme (* course fees are subject to change without prior notice)
Deadline on 13 Oct 2023 (Fri)
2867 8331
2861 0278
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Upcoming Events

Special Announcement: Accept new applications for Oct 2023 intake! There will be practical classes in the computer laboratory.

Predictive Analytics is a branch of Business Analytics. Our professional lecturer will share the contemporary development of AI, such as clustering, chatbot and pattern recognition, and business applications of AI as well as methodologies of Predictive Analytics. Welcome to your online application!


This programme provides students with the practical knowledge of Artificial Intelligence (AI) as well as discuss the application of Predictive Analytics for Business. Moreover, the programme covers the handling of data for data analysis, data visualization, development of AI and forecasting techniques from the business perspectives. Apart from applying the knowledge to solve problems in their workplace, students may consider further their studies in Big Data, Data Analytics, Data Science, AI, FinTech and Quantitative Analysis in future.




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Students under this programme are eligible to apply free membership for Hong Kong Internet and Ecommerce Association (HKIECA).

The association offers talks, workshops and/or seminars related to the Internet and Ecommerce as well as Big Data.

Programme Details

On completion of the programme, students should be able to:
- describe the data preparation and applications of Big Data for data analysis;
- use statistical methods to analyze and visualize business and financial data;
- identify the concepts and framework of AI;
- apply regression, forecasting and simulation for facilitating prediction and decision making; and
- examine applications of AI and predictive analytics to solve business and financial problems.



(1) Mr. Ken Liu, co-founder and CTO of Datatact Ltd, a startup focus on AI, Machine Learning and Big Data analytics. He is a hands on expert in his specialized area for over 10 years.  Prior to Datatact, Ken worked at Citi, HSBC, Goldman Sachs, Deutsche Bank and Credit Suisse as Algo-Trading developer. Ken earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.

(2) Mr. Dexter Ng, a seasoned Financial Risk Manager (FRM) and Chartered Statistician (CStat) with over 7 years of diverse working experience across Banking, Government, and FinTech industries.  With a strong academic background in Statistics and Economics from The University of Hong Kong, Mr. Ng has been able to apply the field of knowledge and run a successful start-up providing data science solutions and consulting services to the Government and SMEs.  With extensive hands-on experience in the application of machine learning, big data, and analytics to real-world solutions, Mr. Ng is passionate about sharing his knowledge and helping students unlock the full potential of data analytics.

(3) Mr. Alan Cheung, PRM, CQF, has solid experience in fintech in top tier investment banks, versed in architecting low latency, high frequency algorithmic trading systems. He is currently a Quantitative Strategist on the Equities Desk in Bank of America Merrill Lynch. Alan has a Masters in Mathematical & Computational Finance from the University of Oxford after graduating with First Class Honours in Mathematics with Statistics for Finance from Imperial College London.

(4) Mr. Jong Hang, currently working at the Bank of America Merrill Lynch in Hong Kong responsible for the Client Management analytics. Prior to that, he has worked in Singapore for 6 years using Big Data and Data Science to help business and government organizations to mine insights from data. He has completed various Data Science projects in Europe, United States and Asia. Jong Hang was also a Cloudera Authorized Trainer from 2012 to 2015. He has taught Cloudera Big Data courses such as Hadoop Administration, Hadoop Developer, Hive, Pig. Jong Hang is also an active learner on Coursera and edX MOOC who has completed more than 50 courses in Data Science, Artificial Intelligence, Mathematics and Statistics, Engineering.

(5) Dr. Garry Luk, a Chartered IT Professional (CITP) of British Computer Society. His major research interest in Business system analysis and design, Big data implementation and application, Information management technology. He has been working on the higher education sector for more than 18 years for teaching and research support.
Moreover, Dr. Luk also as a part-time lecturer since 2004 for Vocational training council, School of Continuing Education Hong Kong Baptist University and Hong Kong University of Professional and Continuing Education on E-commerce, Business information system, System Analysis & Design. Dr. Luk will share and inspired Executives at various levels from his rich research and working experiences.

(6) Ms. Rowena Lai, has extensive experience in business and data analytics in different business sectors. She is currently working in a well-known international bank and leading various data analytics projects. She graduated from the Chinese University of Hong Kong with a Bachelor of Science degree (major in Mathematics and Minor in Economics), and obtained a Master of Science in International Shipping and Transport Logistics as well as a Master of Science degree in Global Supply Chain Management from the Hong Kong Polytechnic University. Ms. Lai is currently a Certified Analytics Professional (CAP) from INFORMS. With her practical experience in data analytics and professional knowledge in financial technology, she teaches "Big Data and FinTech" module under Postgraduate Diploma in Investment Management and Financial Intelligence, Executive Certificate in Big Data and Data Analytics as well as Executive Certificate in Text Analytics and NLP with Financial Technology.

(7) Mr. Cyrus Tsui,  have 10+ years of banking experience in both Hong Kong and London, specialize in valuation, PnL and Risk. Fluent in English, Mandarin and Cantonese. In-depth understanding of complex financial products with programming ability, strong communication skill and solid experience in stakeholder management.

Application Code 2150-EP137A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 1:00pm - 7:00pm
  • Hong Kong Island Campus
  • Kowloon East Campus


Course Content: 

(1) Data preparation and Data Analysis
- Data preprocessing, data cleaning and data transformation
- Processing techniques over Cloud for business and financial data
- Applications of data analysis for business and financial data

(2) Statistical Analysis and Data Visualization
- Introduction to Statistical Analysis
- Data Visualization for business and financial decision making

(3) Applications of Artificial Intelligence (AI) and Predictive Analytics
- Development of AI
- Introduction to machine learning, deep learning and reinforcement learning
- Chatbot and Natural Language Processing for business and finance
- Introduction to Data Mining
- Clustering and Pattern Recognition
- Trendlines and Regression Analysis for forecasting
- Business applications of AI and Predictive Analytics

Assessment method: In-class exercise + group presentation

The Executive Certificate will be conferred to candidates who have attained PASS grade and achieved at least 70% attendance of the programme.

Class Details


Oct 2023 intake 

Lecture Date Time
1 28 Oct 23 (Sat) 13:00 - 19:00
2 4 Nov 23 (Sat) 13:00 - 19:00
3 11 Nov 23 (Sat) 13:00 - 19:00
4 25 Nov 23 (Sat) 13:00 - 19:00
5 2 Dec 23 (Sat) 13:00 - 19:00

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

Entry Requirements

Applicants shall hold:
a)    a bachelor’s degree awarded by a recognized University or equivalent; or
b)   an Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant working experience.

Applicants with other qualification and substantial senior level work experience will be considered on individual merit.

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


Application Fee

HK$150 (Student only needs to pay one time application fee for all EC in Big Data Series)

Course Fee
  • Course Fee: $8800 per programme (* course fees are subject to change without prior notice)


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 the 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 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 (course 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, continuing students of award-bearing programmes, if their programmes offer online service, may also pay their course fees by Online WeChat Pay, Online Alipay and Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.


  • 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 Enrolement Centres and avoid making cheque payment under this circustance.
  • 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 or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder's credit card account.
  • 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.
  • Receipts will be issued for fees paid but HKU SPACE will not be repsonsible for any loss of receipt 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. 

Partner Details


Students under this programme are eligible to apply free membership for Hong Kong Internet and Ecommerce Association (HKIECA).

The association offers talks, workshops and/or seminars related to the Internet and Ecommerce as well as Big Data.

Link of HKIECA: