行政人員證書《大數據,人工智能與投資》 - 香港大學專業進修學院: FinTech and Financial Intelligence, Data Science課程
通告
新型冠狀病毒影響下的課堂安排

在新型冠狀病毒疫情不穩定的狀態下,未來數月可能持續影響我們的課堂安排。學院一向以學員的健康及個人安全為首要考慮,為確保學生的學習進度不受影響,學院有可能需要按有關指引將面授課堂改為網上授課。如出現此等情況,課程組別同事將會儘快聯絡學員有關安排的詳情。如欲了解更多新型冠狀病毒影響下課堂安排之詳情,請參閱學院網頁之 特別通告

關閉特別通告
Main content start

Accounting & Finance FinTech and Financial Intelligence

Executive Certificate in Big Data, A.I. and Investing
行政人員證書《大數據,人工智能與投資》

Course Code
EP103A
Application Code
1965-EP103A
Study mode
Part-time
Start Date
08 Jan 2022 (Sat)
Next intake(s)
Jul 2022
Duration
1 month to 2 months
Language
English supplemented with Cantonese
Course Fee
HK$8300 per programme
Apply Now
Deadline on 22 Dec 2021 (Wed)
Enquiries
2867 8331
2681 0278
Welcome for your application for 2022 February intake! There will be practical classes in computer laboratory.

AI is widely using in analyzing asset prices and predicting stock price movements. Our experienced lecturer will share the applications of AI in quantitative investment and algorithmic trading. Welcome for your online application!

This programme aims to provide students with knowledge in Big Data and Artificial Intelligence technologies and their applications in investment management.  Students are expected to be familiar with different big data analyses and A.I. processes upon completion of the programme.

The programme provides an insight on how the current development in these two areas assist and influence investment decision and behaviour. 
 

ECBDAII

Who would benefit from EC in Big Data, AI & Investing:

  • one who is interested in Big Data and Artificial Intelligence
  • one who has solid investment and quantitative background
  • one who wants to learn how Big Data and A.I. influence investment decision
  • one who wants to apply Big Data available to their investment theories
  • one who is interested to explore the meaning of machine trading

On completion of the programme, students should be able to: 

1.    evaluate different methodologies on Big Data analytics and AI technologies affecting investment decisions;
2.    identify the limits and potentials of data mining and predictive analytics on investing; 
3.    make use of off-the-shelf online Big Data software for investing reference;
4.    apply and analyze using big data concepts and forecast their results through case studies. 

Application Code 1965-EP103A Apply Online Now
Apply Online Now

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

Course Content: 
1.    Introduction to Data Processing and Analyzing on Investing (Application: DATATACT Web)
-     Survey the current industry practices and trends
-     Case studies on the impact of Big Data and AI 
-     Big data processing techniques (such as collection, indexing and storage)


2.    Sentiment Analysis (Applications: Stanford API + DATATACT Web)
-      News and social media sentiment analysis
-     Sentiment and price performance correlation
-      Performing sentiment analysis and filtering


3.    Automated Trading (Applications: Market data and AIgo app)
-          Understanding Algorithmic, Program and High Frequency trading
-          Real-time analytics and data-streaming processing
-          Examples of online real-time data for analysis


4.    Predictive Analytics and Visualisation of results
-          The basics of AI and Machine Learnings 
-          Applying machine learning to predict stock order flow
-          Interpretation of data thru visualization


5.    Challenges of Deep & Reinforcement Learning (ie. Alpha Go) techniques in investing
-          Introducing Alpha-Go and its underlying technologies
-          Limitation on the prediction techniques
-          Managing the trading costs

Assessment method: Continuous assessment (In-class assignments) + Final Assessment (Group presentation & report)

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. Ken Liu, co-founder and CTO of Datatact Ltd, a startup focus on AI, Machine Learning and Big Data analytics. He is a hands on expert in his specialized area for over 10 years.  Prior to Datatact, Ken worked at Citi, HSBC, Goldman Sachs, Deutsche Bank and Credit Suisse as Algo-Trading developer. Ken earned a Master in Computer Science from USC and a Bachelor in Computer Science from University of Warwick.

(2) Dr. Peter Yau has over 10 years of industrial and training experience in both the technical and business domains. He was the IT Director of a consultancy firm, providing advisory and development service to the investment banks, universities, hospitals, government and global suppliers. He was the subject matter expert in one of the big four accounting firms and was invited to give a training program to the government official in an open forum which was funded by the European Union in Ulaanbaatar. He shares his knowledge in information technology by teaching in the tertiary education and conducting research. His doctoral research is Fintech related.

 Time table

2022 Jan intake 

Lecture Date Time
 1 8 Jan 22 (Sat) 13:30-19:30
 2 15 Jan 22 (Sat) 13:30-19:30
 3 22 Jan 22 (Sat) 13:30-19:30
 4 12 Feb 22 (Sat) 13:30-19:30
 5 19 Feb 22 (Sat) 13:30-19:30

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 relevant 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$8300 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.