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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (Financial Data Analytics with Python and Power BI)
證書(單元 : 金融數據分析–Python 及Power BI)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
FN106A
Application Code
2255-FN106A

Credit
6
Study mode
Part-time
Start Date
19 Nov 2024 (Tue)
Next intake(s)
Jan 2025
Duration
30 hours
Language
English
Course Fee
Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
Deadline on 05 Nov 2024 (Tue)
Enquiries
2867 8331
2861 0278
Apply Now

Today and Upcoming Events

Confirm launch for Nov 2024 intake! There are practical classes in the computer laboratory. Financial data analytics is widely applied in analyzing and predicting financial data and asset price movement. Python programming, introduction to Python libraries, financial analytics and model building will be covered. Also, data extraction, transformation and loading using Python and Power BI will be illustrated. Introduction to data analysis expressions (DAX), data visualization and dashboard design using Power BI will be discussed.

Highlights

The programme aims to provide students with essential knowledge of financial data analytics using computational tools. It equips students with practical skills to perform data wrangling and data visualisation using Python and Power BI in the computer laboratory. The programme also illustrates financial analytics and model building, as well as discusses the dashboard design to assist decision-making and improve financial performance. 
 

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Programme Details

Intended Learning Outcomes (ILOs) of the Programme

On completion of the programme, students should be able to

  1. explain the principles of financial analytics and techniques of data analytics;
  2. apply Python for data wrangling and financial model building;
  3. use Power BI for data visualisation and dashboard design; and
  4. perform financial data analytics and evaluate business strategies.
Application Code 2255-FN106A Apply Online Now
Apply Online Now

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

Modules

Syllabus

(1) Principles of financial data analytics

  • Fundamentals of data science and data analytics
  • Overview of technological elements for data analytics
  • Introduction to data wrangling and data cleaning
  • Basic characteristics of financial data and techniques of data analytics

(2) Financial data analytics with Python

  • Overview of the Python and programming platform
  • Basic Python coding: data types, operators, if statement, loop, exceptional handling
  • Introduction to Python library
    • Data wrangling and cleaning for financial data: Pandas, Numpy, Scipy
    • Statistics and financial data visualisation: Matplotlab, Seaborn, plotly
    • Web scraping tools for financial data: Selenium, Beautiful Soup, yfinance, investpy
  • Financial analytics and model building

(3) Financial data analytics with Power BI

  • Introduction to Power BI and the role of business intelligence
  • Exploration of the Power BI desktop interface
  • Data source from Excel and Python for Power BI
  • Overview of data extraction, transformation and loading using Python and Power BI
  • Data manipulation and Power BI desktop queries
  • Introduction to data analysis expressions (DAX)
  • Key performance indicators for decision-making
  • Data visualisation and dashboard design using Power BI
  • Analysis and report in Power BI and storytelling with financial data
  • Business strategies and financial performance improvement

Assessment method: One individual assignment  + Group Project Presentation

Award

Upon successful completion of the programme, students who have passed the assessments with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a “Certificate for Module (Financial Data Analytics with Python and Power BI).”

Teacher

(1) Mr Kevin Leung

Mr. Leung is a seasoned accountant with advanced data analytics and programming skills. He worked at several leading corporations in different industries and supervised teams to drive technological innovation in finance operations. He is also a lecturer, teaching financial analytics and business management courses. He holds an MSc (Distinction) in Business Analytics from the Hong Kong Polytechnic University and a BA (First Class Honours) in Integrated Business and Global Studies from Centennial College. He published a research paper on big data analytics in a reputable journal. Through his professional and academic background, he would like to share his experience in building financial and statistical models by spreadsheet and programming, applying ERP and BI software to data analysis and automating operational processes.

Class Details

Timetable

Lecture Date  Time
1 19 Nov 24 (Tue) 19:00-22:00
2 20 Nov 24 (Wed) 19:00-22:00
3 26 Nov 24 (Tue) 19:00-22:00
4 27 Nov 24 (Wed) 19:00-22:00
5

3 Dec 24 (Tue)

19:00-22:00
6 4 Dec 24 (Wed) 19:00-22:00
7 10 Dec 24 (Tue) 19:00-22:00
8 11 Dec24 (Wed) 19:00-22:00
9 17 Dec 24 (Tue) 19:00-22:00
10 18 Dec24 (Wed) 19:00-22:00

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

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $9900 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 a business, accounting, finance, economics, mathematics, statistics, science, engineering, IT or computer science background would have an advantage.

 

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 (FINANCIAL DATA ANALYTICS WITH PYTHON AND POWER BI)
證書(單元:金融數據分析 - PYTHON 及POWER BI)
COURSE CODE 33C158655 FEES $9,900 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 (Financial Data Analytics with Python and Power BI)

  • 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.