Executive Certificate in Text Analytics and NLP with Financial Technology - HKU SPACE: FinTech and Financial Intelligence, Data Science courses
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Class arrangement during COVID-19


The COVID-19 situation may still be fluid and constantly affect class arrangements in the coming months. The health and safety of our students will always be our top priority. To ensure that students’ academic progress is not affected, the School may substitute face-to-face classes with online teaching if necessary in the event that face to-face classes cannot be held. Our respective Programme Teams will contact the students concerned with details of such arrangements as necessary. For more details on the class arrangement during COVID-19, please refer to the special announcement on the School homepage.

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Accounting & Finance FinTech and Financial Intelligence

Executive Certificate in Text Analytics and NLP with Financial Technology
行政人員證書《金融科技:文字分析與自然語言處理》

Course Code
EP163A
Application Code
1955-EP163A
Study mode
Part-time
Start Date
06 Nov 2021 (Sat)
Next intake(s)
Feb 2022
Duration
2 months to 3 months
Language
English
Course Fee
HK$9000
Apply Now
Deadline on 22 Oct 2021 (Fri)
Enquiries
2867 8331
2861 0278
Accept new application for November intake! There will be practical classes in computer laboratory.

Text mining and textual data wrangling are commonly using in FinTech and data analytics. Also, our experienced lecturer will discuss sentiment analysis and the applications of natural language processing. Welcome for your online application!

The programme aims to cover the latest applications of financial technology by using text analytics and natural language processing (NLP). It provides students with a foundation in collecting, processing, managing and analyzing textual data using computational tools. It discusses the use of NLP, text analytics and machine intelligence. The programme also offers summarization and visualization of results obtained from text analytics and NLP for applications in finance.
 

On completion of the programme, students should be able to
1. identify the main elements of text analytics and natural language processing;
2. examine techniques of text analytics and natural language processing;
3. apply machine intelligence to analyze and visualize textual data using computation tools;
4. discuss the latest applications of text analytics and natural language processing in financial technology.

 
ECTANLPFT
Application Code 1955-EP163A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 1:00pm - 7:00pm

Course Content: 

Introduction to Text Analytics and Natural Language Processing (NLP)

  • Technological overview of text analytics and NLP in finance and investment: text mining, web mining, data mining, information retrieval and NLP
  • Principles of text analytics
    • Key elements of text analytics
    • Textual data wrangling: collecting, importing, organizing and cleaning textual data
    • Text mining and text analytics: web scraping, textual corpora, text processing, tokenization, stemming and stop word removal
  • Essential of natural language processing (NLP)
    • Core elements of NLP
    • Lexical parsing, syntax parsing, semantic parsing 
    • NLP and computational linguistics

 

Machine Intelligence, Text Analytics and NLP in Financial Technology

  • Development of machine intelligence in financial technology: AI, Machine Learning and Deep Learning
  • Introduction to computation tools for text analytics and NLP: R, Python, Tensorflow, Pytorch
  • Basic algorithms from deep learning: linear regressions, SVM
  • Introduction to Neural Network for Text Analytics and NLP: Convolution Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Generative Adversarial Network (GAN)
  • Techniques for text analytics and NLP: bag-of-words, word weighting schemes, document classification, document clustering, sentiment analysis and model building

 

Text Analytics and NLP in Financial Decision Making

  • Real-world financial information and textual datasets
    • Financial texts from corporate disclosures, financial reports, professional periodicals, aggregated news, message boards and social media
    • Summarization of textual data and information
    • Display and visualization of results: word cloud
    • Financial intelligence from analyzed textual data
  • Applications and Issues of text analytics and NLP for financial decision making
    • Statistical and cultural bias in datasets
    • Financial slang and NLP for sentiment analysis
    • Analysis of financial textual data
    • NLP and deep learning for predicting stock price movements
    • Semantic model building for financial forecasting
    • Credit risk analysis using text analytics
    • Implications and limitations of text analytics and NLP in making finance and investment decision
    • Improving financial services with NLP

Assessment method:  Two assignments exercise + group presentation

 

The Executive Certificate will be conferred to candidates who have attained PASS grade and achieved at least 70% attendance of the programme.

Teacher


(1) Ms. Rowena Lai
Ms. Lai has extensive experience in business and data analytics in different business sectors. She is currently working in a well-known international bank and leading various data analytics projects. She graduated from the Chinese University of Hong Kong with a Bachelor of Science degree (major in Mathematics and Minor in Economics), and obtained a Master of Science in International Shipping and Transport Logistics as well as a Master of Science degree in Global Supply Chain Management from the Hong Kong Polytechnic University. Ms. Lai is currently a Certified Analytics Professional (CAP) from INFORMS. With her practical experience in data analytics and professional knowledge in financial technology, she teaches "Big Data and FinTech" module under Postgraduate Diploma in Investment Management and Financial Intelligence, Executive Certificate in Big Data and Data Analytics as well as Executive Certificate in Text Analytics and NLP with Financial Technology.
 
(2) Mr. Clive Yip
Mr. Yip is a practitioner in Data Analytics.  He has 10 years of experience in both Big 4 consulting firms and multinational companies.  He is currently working as a Senior Data Analytics Consultant in a leading insurance company, using Python, SQL and other Big Data technologies to analyse and monitor any non-compliance or fraudulent activities.  He has a Master’s degree in Information Technology from HKUST and a Bachelor’s degree from the University of Southern California.  Before entering the data analytics field, he worked as a financial auditor in Ernst and Young and is a Certified Public Accountant (CPA) in Hong Kong and Canada. 

Timetable

November 2021 intake 

Lecture Date Time
1 6 Nov 21 (Sat) 13:00 - 19:00
2 13 Nov 21 (Sat) 13:00 - 19:00
3

20 Nov 21 (Sat)

13:00 - 19:00
4 27 Nov 21 (Sat) 13:00 - 19:00
5 4 Dec 21 (Sat) 13:00 - 19:00

Remarks :
-Tentative timetable is subject to change and course commencement is subject to sufficient enrollment numbers.
-For your safety and health, please note that the School may substitute face-to-face classes with online teaching if necessary.

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

Applicants with qualifications in quantitative areas (e.g., mathematics, engineering, statistics, computer science, information technology, economics, finance) are preferred. Those with other qualifications and substantial senior level work experience will be considered on individual merit.

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee : HK$9000 (Course fees are subject to change without prior notice)
  • Early Bird Rate : HK$8500 (Early-Bird discounted fee for enrolment on/before application deadline)
  • Alumni Rate : HK$8500 (Alumni from EDEC in Big Data and FinTech Programme Series)

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.