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Accounting & Finance FinTech and Financial Analytics

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)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN093A
Application Code
2465-FN093A

Credit
6
Study mode
Part-time
Start Date
12 Jan 2027 (Tue)
Next intake(s)
Apr 2027
Duration
30 hours
Language
English
Course Fee
Course Fee: $10,200 per programme (* course fees are subject to change without prior notice)
Deadline on 29 Dec 2026 (Tue)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Today and Upcoming Events

Accept New Applications for Jan 2027 intake! There are practical classes in the computer laboratory. By visualizing stock prices using computational tools, technical analysis can be performed professionally, and stock trends can be identified efficiently. Our professional lecturer will share analytical techniques to filter stocks based on technical indicators and predict stock price movement for investment decision-making. Welcome to your online application!

Highlights

The programme aims to provide students with the basic knowledge of stock investment and data analytics, and the essential skills in analysing trends and patterns of stock prices using technical analysis. The programme illustrates techniques of web scraping and data wrangling of stock price data using computational tools. It also discusses technical analysis charts using data visualization. Students can learn how to analyse stock price trends and predict stock price movement to support investment decision-making through practical classes in the computer laboratory.

Programme Details

On completion of the programme, students should be able to

  1. explain the principles of technical analysis and data analytics for stock investment;
  2. analyse patterns on technical analysis charts with the use of technical indicators;
  3. apply computational tools to perform data wrangling, data visualization, statistical analysis and trend prediction of stock prices; and
  4. discuss data-driven decision making and evaluate stock investment performance

 

Application Code 2465-FN093A Apply Online Now
Apply Online Now

Days / Time
  • Tue, Thu, 7:00pm - 10:00pm
Duration
  • 30 hours per programme
Venue
  • Kowloon East Campus
  • Hong Kong Island Learning Centre
  • Kowloon West Campus

Modules

Syllabus

(1) Introduction to technical analysis, data analytics and stock investment  

  • Introduction to data analytics and computational tools
  • Basic analysis of price data for stock investment
  • Principles and assumptions of technical analysis
  • Linkages between technical analysis and behavioral finance
  • Comparison of technical analysis and fundamental analysis for stock investment

(2) Technical analysis and descriptive analytics for stock investment

  • Sources of stock prices and techniques of web scrapping
  • Development of stock price datasets and application of descriptive analytics
  • Data wrangling of stock prices using computational tools
  • Comprehensive stock selection with common filters on price change, turnover, moving average prices and range of technical indicator values
  • Application of technical analysis charts and technical indicators: candlestick charts, Bollinger Bands, MACD curves
  • Visual analytics for stock investment (e.g., price trend in motion)

(3) Stock investment and predictive analytics

  • Overview of stock investment strategies and data-driven decision making
  • Smoothing of stock price trend to facilitate price movement prediction
  • Predictive analytics and stock price analysis
  • Analysis of stock investment by sectors and visualization of investment dashboard
  • Measurement of accuracy and investment performance evaluation

Assessment method: Two in-class exercise + Group Project Presentation

Upon successful completion of the programme, students who have passed the final examination with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a Certificate for Module (Technical Analysis and Data Analytics for Stock Investment).

 

Class Details

Lecture

Date

Time

1

12 Jan 27 (Tue)

19:00-22:00

2

14 Jan 27 (Thu)

19:00-22:00

3

19 Jan 27 (Tue)

19:00-22:00

4

21 Jan 27 (Thu)

19:00-22:00

5

26 Jan 27 (Tue)

19:00-22:00

6

28 Jan 27 (Thu)

19:00-22:00

7

2 Feb 27 (Tue)

19:00-22:00

8

4 Feb 27 (Thu)

19:00-22:00

9

16 Feb 27 (Tue)

19:00-22:00

10

18 Feb 27 (Thu)

19:00-22:00

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

 

 

Teacher Information

Mr Ivan Law

Background

Mr Ivan Law brings over two decades of combined experience in education, applied data science, and the finance industry, with a proven track record of empowering learners to master in-demand technical skills. Holding a BEng in Computer Science from HKUST and an MSc in Financial Management from the University of London, Ivan leverages his interdisciplinary background to make complex data science concepts accessible to students from diverse academic and professional backgrounds. As a part-time lecturer at CityU SCOPE, he has delivered over 2,100 instructional hours across 8 cohorts of adult learners, specializing in Python, Pandas, NumPy, data visualization (Matplotlib/Seaborn/Plotly), and AI/ML foundations. Rooted in rigorous project-based learning, his teaching philosophy prioritizes clarity, practical application, and active engagement. He designs interactive exercises and real-world projects to help learners translate theoretical concepts into actionable skills that meet workplace needs. Complementing his teaching practice is 18+ years of experience in senior roles across the banking and hedge fund industry, where he led teams in operations, risk management, and compliance at both local and US-based hedge fund firms. Serving as Director, Ivan now designs and delivers professional data science training and deploys AI/ML pipelines for SMEs. This hands-on, up-to-date experience building industry-ready solutions ensures his teaching curricula remain current with the latest tools and market demands, which further strengthens his ability to connect analytical rigor with business insights.

Mr Danny Chan

Background

Mr Chan, FRM, is currently a consultant and trainer at a Big Data Consultancy Services Company. He is very professional in teaching big data analytics and data automation for business. He possesses rich experience in financial risk management, information technology and data science and has worked as an IT Manager for over a decade. He is strong in cloud-based solutions, big data technology, data mining and machine learning. Mr Chan has delivered training in data science areas, covering R, machine learning, statistics, database programming, AWS cloud architecture and SAS programming for IT professionals and university graduates for over 2 years. He worked as the Head of BI Data Analytics and R&D Team in Li & Fung Group Company, GBG Asia (HK) Limited, IDS Group Ltd. & LF Asia and so on, devoting himself to IT development and project management.

Mr Chan has obtained a Bachelor of Science Degree in Mathematics from The Chinese University of Hong Kong as well as three Master's Degrees, namely, Risk Management Science from The Chinese University of Hong Kong, Quantitative Analysis for Business from the City University of Hong Kong and Industrial Logistics Systems from The Hong Kong Polytechnic University.

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $10,200 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree awarded by a recognised institution. Those with economics, finance, business, IT or computer science background are preferred.

Applicants with other equivalent qualifications will be considered on individual merit.

CEF

  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
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)
COURSE CODE 33C151243 FEES $10,200 ENQUIRY 2867-8331
Continuing Education Fund Continuing Education Fund
This course has been included in the list of reimbursable courses under the Continuing Education Fund.

Certificate for Module (Technical Analysis and Data Analytics for Stock Investment)

  • This course is recognised under the Qualifications Framework (QF Level [5])

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.