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Accounting & Finance FinTech and Financial Intelligence

Executive Certificate in Big Data and Predictive Analytics

Course Code
Application Code
Study mode
Start Date
02 Jul 2024 (Tue)
Next intake(s)
Jan 2025
1 month to 2 months
Course Fee
Course Fee: $8900 per programme (* course fees are subject to change without prior notice)
Deadline on 18 Jun 2024 (Tue)
2867 8331
2861 0278
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Today and Upcoming Events

Jun 2024

Online Executive Certificate / Diploma Information Seminar - Big Data & FinTech Series (24 Jun 2024)

The recent advances in Big Data and AI have major impact on the investment and trading community.  Now different types of alternative data from news, social sentiment to satellite images can be used to construct and manage investment portfolios. Moreover, Machine Learning is applied to stock price predictions while Reinforcement Learning (Alpha-Go) technique is employed into trading strategies discovery. This programme is suitable for degree holders and Executives who wish to enhance their knowledge and current market practices in the Big Data and FinTech series. Seminar topics: Course details, entry requirements, assessment requirements. This information seminar provides details about: -Executive Diploma in Financial Analytics  行政人員文憑《金融數據分析》 -Executive Certificate in Banking and Financial Technology  行政人員證書《銀行及金融科技》 -Executive Certificate in Big Data and Business Analytics  行政人員證書《大數據與業務分析》 -Executive Certificate in Big Data and Predictive Analytics  行政人員證書《大數據與預測分析》 -Executive Certificate in Big Data, A.I. and Investing  行政人員證書《大數據,人工智能與投資》 -Executive Certificate in Applications of Blockchain in Financial Technology  行政人員證書《區塊鏈在金融科技的應用》 -Executive Certificate in Applied AI and Predictive Analytics for Business  行政人員證書《應用人工智能與商業預測分析》 -Executive Certificate in AI and Deep Learning in Quantitative Finance  行政人員證書《量化投資:人工智能與深度學習》 -Executive Certificate in Applied Business Analytics and Decision Optimization  行政人員證書《應用商業分析與決策優化》 -Executive Certificate in Interpretation and Visualization of Business Big Data  行政人員證書《商業大數據視覺化及資訊演繹》 -Executive Certificate in Financial Decision Making: Big Data and Machine Learning  行政人員證書《財務決策:大數據及機器學習》 -Executive Certificate in Text Analytics and NLP with Financial Technology 行政人員證書《金融科技:文字分析與自然語言處理》 -Certificate for Module (Big Data Governance and Data Compliance)  證書(單元 : 大數據治理及數據合規) -Certificate for Module (Business Analytics and Web Scraping)  證書(單元 : 商業分析及網站擷取) -Certificate for Module (Robotic Process Automation with Business and Financial Applications)  證書(單元:機械人流程自動化於商業與財務應用) -Certificate for Module (Distributed Ledger and Blockchain with Business Applications)  證書(單元 : 分散式帳本與區塊鏈的商業應用) -Certificate for Module (Business Intelligence and Data Automation)  證書(單元 : 商業智能與數據自動化) -Certificate for Module (Business Process Automation with VBA and Python)  證書(單元:商業流程自動化 – VBA及Python) -Certificate for Module (Business Forecasting and Predictive Analytics for Financial Decision Making)  證書(單元:財務決策的商業分析與預測) -Certificate for Module (Technical Analysis and Data Analytics for Stock Investment) 證書(單元 : 股票投資的數據與技術分析) -Certificate for Module (Sustainable Finance and Green FinTech) 證書(單元 : 可持續金融與綠色金融科技) -Certificate for Module (Generative AI, DeFi and Risk Governance) 證書(單元 : 生成式人工智能、去中心化金融與風險管治) -Certificate for Module (Web 3.0 and FinTech) 證書(單元 : 第三代互聯網與金融科技) -Certificate for Module (GenAI and Automation for Finance and Business) 證書(單元 : 生成式人工智能及金融與業務自動化) -Certificate for Module (Financial Data Analytics with Python and Power BI) 證書(單元 : 金融數據分析–Python 及Power BI) -Certificate for Module (AI and ML with Business and Financial Applications) 證書(單元 : 人工智能與機器學習 - 商業與財務應用) -Certificate for Module (Financial Informatics and Data Analytics) 證書(單元 : 金融信息學與數據分析) -Certificate for Module  (Web Application Programming for Finance and Business) 證書(單元:金融與商業網頁應用編程) Unable to join us at the Information Seminar? Email to for One-on-One after-office-hour consultation, by appointment only.

Accept new applications for Jul 2024 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!


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


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 2235-EP105A Apply Online Now
Apply Online Now

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


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.



(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) Dr. Jason Liao
Dr. Jason Liao obtained his Bachelor and Master degrees from Tsinghua University and PhD from HKUST. He is a Qlik Sense Data Architect with certification. He has lots of working experience and wide expertise in big data, business intelligence, machine learning and FinTech innovation. He is proficient in BI data model/dashboard development, R, Python, SQL, etc. During his past working experience, either internal or external training took a rather large portion, and he elicited favorable comments froms trainees.

Class Details


Lecture Date Time
1 2 Jul 24 (Tue) 19:00-22:00
2 4 Jul 24 (Thu) 19:00-22:00
3 9 Jul 24 (Tue) 19:00-22:00
4 11 Jul 24 (Thu) 19:00-22:00
5 16 Jul 24 (Tue) 19:00-22:00
6 18 Jul 24 (Thu) 19:00-22:00
7 23 Jul 24 (Tue) 19:00-22:00
8 25 Jul 24 (Thu) 19:00-22:00
9 30 Jul 24 (Tue) 19:00-22:00
10 1 Aug 24 (Thu) 19:00-22:00

-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.


Application Fee

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

Course Fee
  • Course Fee: $8900 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. 


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.