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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
2265-EP105A
Study mode
Part-time
Start Date
07 Jan 2025 (Tue)
Next intake(s)
Mar 2025
Duration
1 month to 2 months
Language
English
Course Fee
Course Fee: $8900 per programme (* course fees are subject to change without prior notice)
Deadline on 23 Dec 2024 (Mon)
Enquiries
2867 8331
2861 0278
Apply Now

Today and Upcoming Events

Accept new applications for Jan 2025 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 2265-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) 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

Timetable

Lecture Date Time
1 7 Jan 25 (Tue) 19:00-22:00
2 9 Jan 25 (Thu) 19:00-22:00
3 14 Jan 25 (Tue) 19:00-22:00
4 16 Jan 25 (Thu) 19:00-22:00
5 21 Jan 25 (Tue) 19:00-22:00
6 23 Jan 25 (Thu) 19:00-22:00
7 6 Feb 25 (Thu) 19:00-22:00
8 11 Feb 25 (Tue) 19:00-22:00
9 13 Feb 25 (Thu) 19:00-22:00
10 18 Feb 25 (Tue) 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: $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. 

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.