Executive Certificate in Big Data and Predictive Analytics - HKU SPACE: FinTech and Financial Intelligence, Data Science courses
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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. For more details on the class arrangement during COVID-19, please refer to the special announcement on the School homepage.

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Accounting & Finance FinTech and Financial Intelligence

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
1945-EP105A
Study mode
Part-time
Start Date
04 Sep 2021 (Sat)
Next intake(s)
Dec 2021
Duration
1 month to 2 months
Language
English
Course Fee
HK$8000 per programme
Apply Now
Deadline on 20 Aug 2021 (Fri)
Enquiries
2867 8331
2861 0278
Accepting new applications for 2021 September intake! There will be practical classes in computer laboratory.

With the introduction to big data and SQL using R, business trends will be explored using predictive analytics which is useful in formulating marketing strategies. Our experience lecturer will discuss univariate statistical analyses such as hypothesis testing and regression models. Welcome for 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.  

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 1945-EP105A Apply Online Now
Apply Online Now

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

 

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) 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.

Timetable

2021 September intake 

Lecture Date Time
1 4 Sep 21 (Sat) 10:00 - 13:00 ~ 14:00 - 18:30
2 11 Sep 21 (Sat) 10:00 - 13:00 ~ 14:00 - 18:30
3 18 Sep 21 (Sat) 10:00 - 13:00 ~ 14:00 - 18:30
4 25 Sep 21 (Sat) 10:00 - 13:00  ~ 14:00 - 18:30

*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.

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$8000 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.

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 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.