Executive Certificate in Big Data and Predictive Analytics - HKU SPACE: FinTech and Financial Intelligence courses
Class arrangement during COVID-19

The COVID-19 situation may still be fluid and constantly affect class arrangements in the coming months. The health and safety of our students will always be our top priority. To ensure that students’ academic progress is not affected, the School may substitute face-to-face classes with online teaching if necessary in the event that face to-face classes cannot be held. Our respective Programme Teams will contact the students concerned with details of such arrangements as necessary.

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Executive Certificate in Big Data and Predictive Analytics

Course Code
Application Code
Study mode
Start Date
To be advised
Next intake(s)
Jan 2021
1 month to 2 months
Course Fee
HK$7000 per programme
Apply Now
Deadline on 07 Oct 2020 (Wed)
2867 8331
2861 0278
Confirmed launch with commencement date on 10 Oct 20 (Sat)! Accepting new applications for October 2020 intake!

Do not miss the valuable insights from our professional teacher in this field!!!

加長版預測分析課程, More case studies, More methodologies for Data Mining & Modeling!
一致好評導師 Alex Hung 再次講課. Basic Coding/Logic concept/knowledge would be helpful.

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.  



AI崛起 數據分析師最吃香 by Skypost

Why is Predictive Analytics important?  by SAS

Predictive analytics use statistical analysis, data modelling, real-time scoring, and machine learning to detect trends for forecasting….  by CGMA

The importance of big data and analytics in the era of digital transformation  by itproportal.com

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.


  • 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).
  • Dr. George Ng is a data science practitioner who received his doctorate in Biotechnology from the University of Queensland Australia. He actively consults in the application of machine learning and artificial intelligence in Manufacturing, Food & Beverage, Hotels, Logistics & Transportation, Retail, Energy, Consumer Goods, Big Pharma industries.  He is a visiting scholar at the Hong Kong University of Science and Technology for full-time MSc in investment management and teaches Machine Learning with Python. He was the founder and CEO of 2 previous startups.
Application Code 1850-EP105A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 10:00am - 1:00pm - 2:00pm - 6:30pm
  • 30 hours per module
  • 4 meeting(s)
  • 7.5 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.

October 2020 intake 

Lecture Date Time
1 10 Oct 20 (Sat) 10:00 - 13:00 ~ 14:00 - 18:30
2 17 Oct 20 (Sat) 10:00 - 13:00 ~ 14:00 - 18:30
3 24 Oct 20 (Sat) 10:00 - 13:00 ~ 14:00 - 18:30
4 31 Oct 20 (Sat) 10:00 - 13:00  ~ 14:00 - 18:30

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

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. 

Application Fee

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

Course Fee
  • Course Fee : HK$7000 per programme (Course fees are subject to change without prior notice)

Online Application Apply Now

Application Form Download Application Form

Enrolment Method

HKU SPACE provides 24-hour online application and payment service for students to make enrolment for most open admission courses (courses enrolled on first come, first served basis) and selected award-bearing programmes via the Internet.  Applicants may settle the payment by using either PPS, VISA or Mastercard online.

  1. Complete the online application form

    Applicant may click the icon Apply Now on the top right hand corner of the programme/course webpage to make online application, and then follow the instructions to fill in the online application form.

    Some programmes/courses may be admitted by selection, and may require applicants to provide electronic copy of any required documents (e.g. proof of qualification) as indicated on the programme/course webpage.  Only file format in doc, docx, jpg and pdf are supported. 

  2. Make Online Payment

    Pay the programme/course fees by either using:

    PPS via Internet - You will need a PPS account and a PPS Internet password. For information on how to open a PPS account and how to set up a PPS Internet password, please visit http://www.ppshk.com.

    Credit Card Online Payment - Course fees can be paid by VISA or Mastercard including the “HKU SPACE Mastercard”.

To know more about online enrolment and payment, please refer to the user guide of Online Enrolment and Payment:


In Person / Mail

For first time enrolment

Applicants must provide all the required information on the application form and any additional information as required after the intial application assessment. Otherwise the School may not be able to process the admission/enrolment further.

  1. For first come, first served short courses, complete the Application for Enrolment Form SF26 and bring or post the completed form(s), together with the appropriate application/course fee(s) and any required supporting documents to any of the HKU SPACE enrolment centres.  
  2. Award-bearing and professional courses may require other information. Forms are usually available at the enrolment centres or on request from programme staff. Bring or post the completed form(s), together with the appropriate application/course fee(s) and any required supporting documents to any of the HKU SPACE enrolment centres.

For continuing enrolment in the same course

In person or by post
  1. The standard ‘Enrolment/Payment Slip’ is designed for students of award-bearing programmes or remaining programmes in a suite of programmes requiring continuing enrolment and it applies to most programmes.
  2. Students should complete the “Enrolment/Payment Slip” which will be made available by relevant programme staff and return the slip to any HKU SPACE enrolment centre or post it to the relevant programme staff with appropriate fee payment.

If you are in doubt about the procedures, please check the individual course details, or contact our programme staff or enrolment centres. 

Please note the followings for programme/course enrollment:

  1. To make an application online, you will need a computer with connection to the Internet and a web browser with JavaScript enabled. Internet Explorer 5.01 or above is recommended for the web browser.
  2. Applicants should not leave the online application idle for more than 10 minutes.  Otherwise, applicants must restart the application process.
  3. Only S-MILES and Early Bird Discount are supported in Online Applicants (Application).  To enjoy other types of discount, please visit one of our enrolment centres.
  4. During the online application process, asynchronous application and payment submission may occur.  Successful payment may not guarantee successful application.  In case of unsuccessful submission, our programme staff will contact you shortly.
  5. Applicants are reminded that they should only apply for the same programme/course once through counter or online application.
  6. For online enrolment, payment confirmation page would be displayed after payment has been made successfully.  In addition, a confirmation email would also be sent to your email account.  You are advised to keep your payment confirmation for future enquiries.
  7. Fees paid are not refundable except as statutorily provided or under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment).
  8. If admission is by selection, the official receipt is not a guarantee that your application has been accepted.  We will inform you of the result as soon as possible after the closing date for application.  Unsuccessful applicants will be given a refund of programme/course fee if already paid.


The School provides a platform for online services for a selected range of products it offers. While every effort is made to ensure timeliness and accuracy of information contained in this website, such information and materials are provided "as is" without express or implied warranty of any kind. In particular, no warranty or assurance regarding non-infringement, security, accuracy, fitness for a purpose or freedom from computer viruses is given in connection with such information and materials.

The School (and its respective employees and subsidiaries) is not liable for any loss or damage in connection with any online payments made by you by reason of (i) any failure, delay, interruption, suspension or restriction of the transmission of any information or message from any payment gateways of the relevant banks and/or third party merchants for processing credit/debit/smart card or other payment facilitation mechanism; (ii) any negligence, mistake, error in or omission from any information or message transmitted from the said payment gateways; (iii) any breakdown, malfunction or failure of those gateways in effecting online payment service or (iv) anything arisen out of or in connection with the said payment gateways, including but not limited to unauthorised access to or alternation of the transmission of data or any unlawful act not permitted by the law.

Payment Method
1. Cash or EPS

Cash or EPS are accepted 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 write the programme title(s)  and the applicant’s name on the back of the cheque. You may either:

  • in person by submitting the payment, completed form(s), and required supporting documents to any of our enrolment centres; or
  • by mailing the above documents to any of our enrolment centres, specifying “Course Application” on the envelope. 
3. VISA/MasterCard

Course applicants, who are holders of HKU SPACE Mastercard, can enjoy a 10-month interest-free instalment period for courses of HK$2,000 and over. For enquiries, please contact our enrolment centres.

4. Online payment

Online payment for short courses (first come, first served) and selected award-bearing programmes is available using PPS, VISA or Mastercard. Please refer to the Online Services page on the School website.


  1. For general and short courses, applicants may be required to pay the course fee in cash or by EPS, Visa or Mastercard if the course is to start shortly.
  2. 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, cheque or online PPS will be reimbursed by a cheque; fees paid by credit card will be reimbursed to credit card account used for payment.
  3. 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 teams for details.
  4. Fees and places on courses are not transferrable. 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.
  5. HKU SPACE will not be responsible for any loss of payment, receipt, or personal information sent by mail.
  6. For additional copies of receipts, 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. Such copies will normally be issued at the end of a course.