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Accounting & Finance FinTech and Financial Analytics

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》

Course Code
EP129A
Application Code
2390-EP129A
Study mode
Part-time
Start Date
06 Jun 2026 (Sat)
Next intake(s)
Dec 2026
Duration
1 month to 2 months
Language
English
Course Fee
Course Fee: $9500 per programme
(*course fees are subject to change without prior notice)
Deadline on 26 May 2026 (Tue)
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 Jun 26 intake! Don't miss the chance. Come and join us! There are practical classes in the computer laboratory. The programme uses Tableau to introduce data wrangling, data modelling, and data visualization. Our professional lecturer will illustrate various business, sales, and marketing analyses. Also, storytelling and the selection of data and chart for business presentations will be discussed. Welcome to your online application!

Highlights

This programme aims to provide students with the basic concepts and knowledge about Big Data and to develop their skills in interpreting Big Data. It provides a practical approach for the students to apply statistical methods to analyze data and to equip them with techniques to perform data visualization for business and financial Big Data.
 

ECIVBBD

You will learn the following techniques with Tableau Desktop:
·       Design of Management Dashboard
·       Top N / Bottom N Analysis
·       Visual Exception Highlighting
·       Sales Forecasting and Trend Analysis
·       Actual and Target Comparison with Bullet Charts
·       Market Basket Analysis
·       New Customer Analysis
·       Scatter Plot of Sales and Profit
·       Pareto Distribution of Sales
·       Moving Average Analysis and Bollinger Band applicable to stock price and sales volatility
·       Financial Analysis with YTD, QTD, MTD, Rolling Sum, Compound Growth Percentage
·       Rank Analysis with Bump Chart
·       Tree Map, Motion Chart, Bubble Chart, Box-and-Whisker Chart and their Business Applications
·       Storytelling with Views for Presentation
·       Sharing Views with Tableau Public

You will be able to learn each of the above techniques with a hands-on practical approach and no programming skill is assumed. Also, the programme will give you a brand new idea of interpreting business in a top-down manner and collecting correlations visually without looking into huge volume of data.

Programme Details

On completion of the programme, students should be able to:
- Explain Big Data concepts and explore the challenges and opportunities in business applications
- Interpret business and financial data and perform analysis using statistical methods
- Apply computer software to visualize the Big Data
- Analyze the Big Data from business and financial perspectives

Application Code 2390-EP129A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 1:00pm - 7:00pm
Duration
  • 30 hours per module
  • 5 hours per session
Venue
  • Hong Kong Island Campus
  • Kowloon East Campus
  • Kowloon West Campus

Modules

Course Content

(1) Introduction to Big Data and Data Wrangling

(a)  Concepts of big data and the domain of data technologies

(b)  Introduction to data preparation, data visualization and visual analytics
- Data cleansing
- Data transformation
- Data consolidation
- Data automation
- Report automation and dashboard design
(c)  Comparison between common Business Intelligence (BI) tools

 

(2) Concept of Dashboard Design

(a)  Factors of a good dashboard design
(b) Strength of Tableau as a visual analytics tool
(c) Dashboard design for dynamic analysis
(d) Chart design with motion

 

(3) Data Visualization and Interpretation

(a)  Practice with Tableau
- Introduction to Tableau (versions, components, licenses and pricing)
​- Design of management dashboard
​- Top N / bottom N analysis
​- Visual exception highlighting
​- Sales forecasting and trend analysis
​- Actual and target comparison with bullet charts
​- Market basket analysis
​- New customer analysis
- Scatter plot of sales and profit
- Pareto distribution of sales
- Moving Average with YTD, MTD, rolling sum, compound growth percentage
- Rank analysis with bump chart
- Motion chart, bubble chart, Box-and-Whisker chart and their business use
(c) Business applications
- Expense control dashboard
- Income statement dashboard with breakdown and trend analytics
- Payroll analytics dashboard
- Stock price analytics dashboard

Assessment method: in-class exercises + group presentation

The Executive Certificate will be conferred to candidates who pass in continuous assessment and final assessment as well as achieved at least 70% attendance of the programme.

 

Teacher

1) Mr Chung
Mr Chung is a specialist in Machine Learning, Statistical Analysis and Data Science. He received his Bachelor and Master Degree in Mathematics from the University of Toronto. He had been a Mathematics and Statistics lecturer in HKUSPACE Community College for more than six years. Since 2013, he became interested and has been doing research in Data Science and Machine Learning. Coming from an academic background, and then working as a machine learning engineer and data scientist, Mr Chung likes to discuss Data Science and Machine Learning from both theoretical and practical perspectives.

2) Mr W. C. Chan
Mr W. C. Chan, a passionate and highly committed data science and computer professional, Mr Chan sees the importance of lifelong learning and keeps himself abreast of the latest data technologies. He is highly proficient in the areas of visual analytics, business intelligence (BI) solutions, statistical analysis, data science, machine learning and cloud-based computing.
Mr Chan graduated from the Mathematics Department in CUHK. He is a seasoned data analytics professional with a strong background in IT, Retail and Supply Chain Industries. He obtained three master’s degrees from three universities, namely Risk Management Science from CUHK, Quantitative Analysis for Business from the City University of HK and Industrial Logistics Systems from Hong Kong Polytechnic University.
In 2021, Mr Chan accredited the title of Tableau Certified Associate Consultant. He is also a principal consultant for a data technology consulting services company, specialized in implementing BI solutions and report data automation.

2) Miss Nancy Choi

Miss Nancy Choi, A global Project Management Team Lead in one of the industry leaders of a hotel group chain. She has hands-on experiences in data analytics, project management, web development and AI technology. 

She earned a AI Bachelor design from the University of Hertfordshire and a Master Degree of Business Administration from the University of Hong Kong.

Class Details

Timetable

Jun 2026 intake

Lecture Date Time
1 6 Jun 26 (Sat) 13:00-19:00
2 13 Jun 26 (Sat) 13:00-19:00
3 27 Jun 26 (Sat) 13:00-19:00
4 4 Jul 26 (Sat) 13:00-19:00
5 11 Jul 26 (Sat) 13:00-19:00

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: $9500 per programme
    (*course fees are subject to change without prior notice)

Entry Requirements

Applicants shall hold:
-A bachelor’s degree awarded by a recognized University or equivalent; or
-An Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant working experience.

Applicants with statistical background are preferred. Those with other qualification and substantial senior level work experience will be considered on individual merit.

**Please upload copy of HKID and proof of qualification 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.