Main content start
Change.每天多學一點 改變.可大可小

會計及金融 金融科技及金融分析

金融科技及金融分析

金融科技的發展日益重要,將影響著金融業的未來。根據最新的施政報告,香港政府大量撥款支持創新和科技拓展,目的將香港提升為智能城市。我們預計社會金融科技專業人士的需求將不斷增加。為滿足市場需求,我們提供有關金融科技、大數據、人工智能等課程,以助專才發展。

Final Call      Whats' New

金融科技及金融分析課程

Programmes Type

課程類別

微證書

開課日期

上課日期

學費資助

地點

香港島

九龍

訂閱 e-資訊
The programme aims to provide students with essential knowledge of robotic process automation (RPA) in streamlining workflow and improving business operations. It covers the design, development and implementation of RPA with illustrations using computational tools. Practical applications and cases of RPA for business and finance will be discussed.  
 
PT
Start 23 NOV 2024 (SAT)
Duration 1 month to 2 months
Fee HK$9600
The programme aims to provide students with the essential knowledge of business intelligence and data automation. It illustrates various techniques of data preparation, data transformation and data automation using computational tools. The programme also discusses real-life cases related to the usage of business intelligence, practical applications and implications of data automation in business. 
PT
Start 30 NOV 2024 (SAT)
Duration 30 hours
Fee Course Fee: $9500 per programme (* course fees are subject to change without prior notice)
The programme aims to provide students with the contemporary knowledge of distributed ledger and blockchain under the continuous technological advancement. It illustrates the development of smart contracts using computational tools and discusses a practical implementation of blockchain in business. The programme also covers the future development of distributed ledger and blockchain and their implications in business. 
PT
Start 05 DEC 2024 (THU)
Duration 30 hours
Fee Course Fee: $10000 per programme (* course fees are subject to change without prior notice)
This programme aims to provide students with knowledge about Artificial Intelligence and Deep Learning in Quantitative Finance as well as their latest developments and applications to finance and investment. It covers various learning algorithms and neural networks as well as machine intelligence to facilitate finance and investment decision making.
PT
Start 07 DEC 2024 (SAT)
Duration 2 months to 3 months
Fee Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
The programme aims to provide students with the latest development of Financial Technology (FinTech) and the contemporary issues related to Banking and Financial Services sectors. It offers knowledge about the various technological applications to enhance the competitive edges of banks, investment and securities firms. In addition, security and regulatory issues will be covered in this programme.
PT
Start 07 DEC 2024 (SAT)
Duration 2 months to 3 months
Fee Course Fee: $9900 per programme (* course fees are subject to change without prior notice)
This programme aims to provide students with knowledge in Big Data and Business Analytics for management decision-making. Students are expected to be familiar with different big data analyses, tools and methodologies. The programme provides an insight on how business world is using Big Data to improve their business models. 
 
PT
Start 07 DEC 2024 (SAT)
Duration 1 month to 2 months
Fee Course Fee: $9200 per programme (* course fees are subject to change without prior notice)
This programme aims to provide students with updated knowledge of Blockchain and its practical applications in the finance and investment fields. It gives an overview of the Blockchain market and introduces students to the basic concept and jargons of Blockchain. The programme also provides the latest market landscape, insight and discussion on the application of Blockchain from the regulatory and legal perspectives.
 
PT
Start 04 JAN 2025 (SAT)
Duration 1 month to 2 months
Fee HK$9200
Programme Objectives
The programme aims to equip students with knowledge and impact of digitalisation on tax administration and operation.
 
 
Programme Structure and Delivery
The proposed new Executive Certificate in Tax Digitalisation will be a 30-hour short course. Students can learn both concepts and theories about the impact of digitalisation on taxation through lectures and case-studies.  Practitioners will be invited to share their experience through the guest lectures. 
 
Medium of instruction is English, supplemented with Cantonese.
 
PT
Start To be advised
Duration 2 months to 3 months
Fee HK$7,000
This programme aims to impart inter-disciplinary knowledge of quantitative finance and machine intelligence to students who are interested in financial analytics and algo trading. It examines contemporary elements in Environmental, Social and Governance (ESG) investing, financial risks and investment portfolios. It also discusses the applications of computational tools to analyse quantitative data and qualitative data, build financial models, perform financial analysis and text analytics to assist investment decision making. The programme illustrates the applications of artificial intelligence (AI) and machine learning to perform financial analytics as well as the usage of algo trading in implementing quantitative investment strategies.
 
 
 
PT
Start 31 OCT 2024 (THU)
Duration 1 year to 2 years
Fee Module fee: $11,000 (course fees are subject to change without prior notice)
2 installment-:1st- three modules: $33,000 and 2nd- three modules: $33,000
The programme aims to: 
  1. impart financial and investment management knowledge and skills to students to enhance their financial decision making;
  2. facilitate students to understand and analyze contemporary issues as well as the latest development in the financial world;
  3. prepare students to sit for the CFA examinations based on the Candidate Body of Knowledge;
  4. equip students with the latest technologies on Big Data and Artificial Intelligence for financial industry;
  5. stimulate students to apply financial intelligence to perform investment management.
PT
Start 02 NOV 2024 (SAT)
Duration 1 year to 2 years
Fee Course Fee: $8200 per module (* course fees are subject to change without prior notice)