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Accounting & Finance FinTech and Financial Analytics

Executive Certificate in Big Data and Predictive Analytics
行政人員證書《大數據與預測分析》

Course Code
EP105A
Application Code
2370-EP105A
Study mode
Part-time
Start Date
03 Feb 2026 (Tue)
Next intake(s)
Apr 2026
Duration
1 month to 2 months
Language
English
Course Fee
Course Fee: $9200 per programme (* course fees are subject to change without prior notice)
Deadline on 23 Jan 2026 (Fri)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

10
Dec 2025
(Wed)

How to Design a Strong-Stock Analytics Dashboard System (强勢股分析系統)? (10 Dec 2025)

To design a stock price analytics system, we need to do the following: Collect historical stock prices Transform the collected stock price record to an appropriate format for presentation Present the transformed stock price datasets in a useful layout to facilitate analytics and investors’ review.   In this talk (webinar), the speaker will showcase how to design a Strong Stock Analytics Dashboard with a BI approach. This would give you a fresh view of the practical use of data automation and data visualization techniques.   During this webinar, you will explore how a Strong Stock Analytics Dashboard will help you to: review the recent trend of HSI identify the strong stocks and weak stocks based on a specified definition of price momentum compare the ratio between the strong stocks and weak stocks according to your selected price momentum definition do sectoral analysis of the strong / weak stocks   This is an advanced application of data analytics techniques with common financial data.  You will find this webinar inspiring and will give you food for thought on how to make use of learnt data techniques for financial stock investment analysis.   Sample Screenshots below:   Related Programme Links: Certificate for Module (Technical Analysis and Data Analytics for Stock Investment) - HKU SPACE: FinTech and Financial Intelligence, Data Science courses https://hkuspace.hku.hk/prog/exe-cert-in-interpretation-and-visualization-of-business-big-data https://hkuspace.hku.hk/prog/cert-for-module-business-intelligence-and-data-automation

17
Dec 2025
(Wed)

Any correlation between Bitcoin, Ethereum and Gold? And now Stablecoin Explained (17 Dec 2025)

Bitcoin and Ethereum are the most dominant cryptocurrencies, both accumulative account for over 90% in term of market capitalization excluding stablecoin, out of more than two thousands currently in the market. They are both in a form of digital asset that trades via various DEX or centralizated regulated trading platforms. However there are quite many key differences among them though. Bitcoin (BTC) is designed as a monetary storage (some proclaim as alternative of Gold) and medium of transaction and as an alternative to fiat currency. Ethereum (ETH), otherwise, is intended for complex smart contracts or dApps which contribute and act as key infrastructure of the emerging Web3.0 future. In light of recent rapid further innovation (like staking protocol) and adoption, the price of BTC and ETH have been risen more than double in past 12 months and also exhibited a huge volatility. The speaker will give a brief introduction of above crypto with some attention drawn to the relationship and correlation among Bitcoin, Ethereum, Gold, XRP and S&P500 – as shown in below charts. The speaker will then also talk about the latest development and impacts of the recently passed GENIUS Act in U.S. and the Stablecoins Ordinance (Cap. 656) in HK. To say, Stablecoin per se. is NOT referring the price to be fixed or stable, it’s referring to link or collateralize by some tangible asse shifting from no intrinsic value issue. At 10 Oct 2025, one of most selloff in crypto, USDe has experienced flash crash to as low as 0.65 USDEUST, per shown below. Source: Bloomberg   Language: Cantonese (Supplemented with English)

Accept New Applications for Feb 2026 intake! There will be practical classes in the computer laboratory. Predictive analytics is an essential branch of data analytics. This programme will introduce data preprocessing, data transformation, data mining, SQL programming and R programming. Also, statistical analysis, hypothesis test and regression will be discussed. Our experienced lecturer will share the practical application of predictive analytics from practitioner viewpoints. Welcome to your online application!

Highlights

This programme aims to provide students with an in-depth knowledge in Big Data concepts and to develop their skill sets in setting up hypothesis models in Predictive Analytics. The objective is to provide an overview of data mining process and to pinpoint the potential and limitations of predictive analytics within a business setting.  

Programme Details

ECBDPA

On completion of the programme, students should be able to:
1.     apply knowledge and skills in the procedure of processing and cleaning of Big Data;
2.     build simple hypothesis modelling to gain insights from voluminous data within a business setting;
3.     identify the limits and potentials of data mining and predictive analytics;
4.     utilize existing Big Data algorithms and tools made available online for predictive analysis;
5.     self-explore commonly available off-the-shelf Big Data tools, algorithms and methodologies;
6.     differentiate the role of Data Scientist from Business Analyst.

Application Code 2370-EP105A Apply Online Now
Apply Online Now

Days / Time
  • Tue, Thu, 7:00pm - 10:00pm
Duration
  • 30 hours per module
  • 10 meeting(s)
  • 3 hours per meeting
Venue
  • Hong Kong Island Campus
  • Kowloon East Campus
  • Kowloon West Campus

Modules

Course Content


Data preprocessing
-  Data mining
-  Data cleaning
-  Handling missing data
-  Identifying misclassifications
-  Data transformation
-  Flag variables
-  Transforming categorical variables into numerical variables
-  Removing useless variables

Exploratory Data Analysis (EDA)
-  Analyzing data sets to summarize their main characteristics
-  Initial data analysis (IDA) to check assumptions for model fitting and hypothesis testing, handling missing values and make transformations of variables

Univariate Statistical Analysis
-  Data mining to discover knowledge in data
-  Statistical approaches to estimation and prediction
-  Statistical tools for testing hypotheses and deriving estimates
-  Confidence interval estimation of mean
-  Hypothesis testing
-  Access strength of evidence against Null Hypothesis
-  Regression Models

Prediction Effect
-  The limits and potential of predictions
-  Financial Services Case Studies

Big Data Tools and Algorithm Exploration
-  Usage of different off-the-shelf tools & algorithm
-  Additional Freewares introduction for predictive analysis

Role of Data Scientist

Challenges and opportunities with Big Data
-     Data acquisition and recording
-     Information extraction and cleaning
-     Data integration, aggregation and representation
-     Query processing, data modelling and analysis
-     Interpretation
-     Heterogeneity and incompleteness
-     Scale
-     Timeliness
-     Privacy
-     System architecture

The popular Big Data & Predictive Analytics Tools & Technique
-  Usage of different off-the-shelf tools & algorithm
-  Additional Freeware introduction for predictive analysis

Exploratory Data Analysis Overview
-  Data profiling & cleaning
-  Initial data analysis to check assumptions for model fitting and hypothesis.

SQL Programming & R Programming Overview
-  Query processing by SQL
-  Predictive Modeling by R

Practical Predictive Modeling Overview
-  Regression Models Overview

Project & Case Studies

Assessment method: class participation + assignment
 

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

 

Teacher

(1) Mr Alex Hung

Mr Hung, Data Analytics Manager APAC at an international insurance firm, is a seasoned Data Analytics professional with more than 10 years of project experience in data analytics (Fraud Risk Analytics / Customer Analytics / Performance Management / Balance Scorecard / Business Intelligence / Data mining / Big data) solution design and development. He has in-depth knowledge and experience in the Banking and Insurance industries and proven track record of shaping and delivery complex large-scale data analytics projects. Mr. Hung received an MBA from CUHK and is a Certified Project Management Professional (PMP).

(2) Mr Gary Chong

Mr Gary is a seasoned professional in Hong Kong’s financial ecosystem since 2008, focusing on the banks’ supervision.  His role involves assessing capital adequacy frameworks, validating internal risk models (IRB), and ensuring regulatory compliance in credit risk modelling.  As a key representative in the Basel Committee’s stress-testing and banking book task force group, he functions like a regulatory “enzyme”, facilitating international financial stability.  Beyond his core role, Gary serves as a lecturer on risk management at CUHK.  Gary is also a columnist, analysing economic trends with evolutionary insight. Previously, he developed IRB models in global banks, acting as a “genetic engineer” of financial risk framework.  He holds an MPhil in Economics and a BSc in Statistics.

Class Details

Timetable

Lecture Date Time
1 3 Feb 26 (Tue) 19:00-22:00
2 5 Feb 26 (Thu) 19:00-22:00
3 10 Feb 26 (Tue) 19:00-22:00
4 12 Feb 26 (Thu) 19:00-22:00
5 24 Feb 26 (Tue) 19:00-22:00
6 26 Feb 26 (Thu) 19:00-22:00
7 3 Mar 26 (Tue) 19:00-22:00
8 5 Mar 26 (Thu) 19:00-22:00
9 10 Mar 26 (Tue) 19:00-22:00
10 12 Mar 26 (Thu) 19:00-22:00

Remarks:
-Tentative timetable is subject to change, and course commencement is subject to sufficient enrollment numbers.
-To ensure that students’ academic progress is not affected, the School may substitute face-to-face classes with online teaching if face-to-face classes cannot be held.

Fee

Application Fee

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

Course Fee
  • Course Fee: $9200 per programme (* course fees are subject to change without prior notice)

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 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. 

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.