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Accounting & Finance Financial Services and Insurance

CFA Practical Skills Module Workshop Series (Python, Data Science & AI)

Course Code
FINA9369
Application Code
2190-1739NW
Study mode
Part-time
Start Date
06 Jun 2024 (Thu)
Duration
9 hours
Language
Cant, supp with English (lecture materials in Eng)
Course Fee
HK$3,600
Deadline on 31 May 2024 (Fri)
Enquiries
2867 8468
2861 0278
Apply Now

Highlights

This is a 9-hour short course to focus on CFA Practical Skills Module.

Students will follow the data science workflow from financial data ingestion to training artificial neural networks. Also, students will have the opportunity to pull financial data and use the standard tools and techniques to prepare it to deliver insights, work through an example of forecasting percentage change in EPS, and explore a common natural language processing task of sentiment analysis.

Programme Details

Teachers

(1) Dr Lai Man-Kit, CFA®

Dr Lai is currently a professional trainer at Executive Training and Management Consultancy as well as a visiting scholar at HKUST.  Dr. Lai has extensive knowledge in teaching adult continuing education. He was also an Assistant Professor at City University from 1994-2000. Dr Lai has taught CFA examination preparatory programmes and finance postgraduate diploma programmes at HKU SPACE for over six years.

(2) Dr Joseph Chan

Dr Chan is an experienced trainer and consultant in the field of finance. He has been teaching numerous courses at the postgraduate level and providing consultancy to different financial institutions. He obtained his doctoral degree in finance at the University of Mississippi. Before returning to Hong Kong, Dr Chan served as a US research analyst and adjunct professor. Dr Chan has taught the CFA examination preparatory programmes at HKU SPACE for over five years.

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

  1. Use Jupyter Notebook for developing, presenting, and sharing data science and artificial intelligence projects;
  2. Explain text data encoding, tokenisation, and feature engineering;
  3. Train and evaluate feedforward and recurrent artificial neural networks to solve regression and classification machine learning problems;
  4. Explore the underlying theory, intuition, and mathematics behind artificial neural networks and deep learning;
  5. Assess the performance of trained machine learning regression and classification models using various key performance indicators (KPIs);
  6. Demonstrate hyperparameters optimisation using GridSearchCV to achieve optimal machine learning model performance;
  7. Apply feature engineering and data cleaning strategies for machine learning and data science applications;
  8. Use scikit-learn library to build, train, and test machine learning models using real-world datasets; and
  9. Describe simple and multiple linear regression models and the roles of dependent and independent variables in the model.
Application Code 2190-1739NW Apply Online Now
Start Date 06 Jun 2024 (Thu)
Apply Online Now

Venue

Modules

Syllabus:

- Python Programming Fundamentals Review

- Data Collection, Wrangling and Feature Engineering in Machine Learning

- Financial Forecasting Using Machine and Deep Learning

- Natural Language Processing (NLP) in Python

 

Class Details

2024 June INTAKE (ACCEPT NEW APPLICATION)

The June 2024 Class is Scheduled for Thursday from 19:00 - 22:00.

Venue: HK Island

Teacher: Dr. Joseph Chan

Lecture Date Time
1 06 Jun 2024 (Thu) 19:00 - 22:00
2 13 Jun 2024 (Thu) 19:00 - 22:00
3 20 Jun 2024 (Thu) 19:00 - 22:00

* The above tentative schedule's for reference only.  Schedule details will be released one week before the commencement date of the class.
** Please inform that if there is inadequate number of applicants, the class may be subject to cancellation.

***A statement of attendance will be issued to students who have achieved at least 70% of attendance.

Fee

Course Fee
  • HK$3,600

Entry Requirements

Applicants should hold a degree awarded by a recognised institution.

Applicants should check with the CFA Institute that they are eligible to attempt the examination.

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 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.