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ENGG1120/ESTR1005 Linear Algebra for Engineers 線性代數及其工程應用
This course aims at introducing students to the fundamental concepts and methods in linear algebra, which are key to many fields of engineering. Topics include systems of linear equations, Gauss elimination, matrix factorization, matrices and their operations, determinants, eigenvalues and eigenvectors, diagonalization, vector space, the Gram-Schmidt process, and linear transformation.
本科教授線性代數的基本概念與方法，以及其在工程上的應用。內容包括：線性方程組、高斯消去法、矩陣分解、矩陣及其運算、行列式、特徵值及特徵向量、對角化、向量空間、格拉姆–施密特正交化和線性變換。
ENGG1130/ESTR1006 Multivariable Calculus for Engineers 多元微積分及其工程應用
This course aims at introducing students to fundamental concepts and methods in multivariable calculus, which provide tools for solving engineering problems. Topics include functions of several variables, curves and surfaces, partial derivatives, Taylor’s formula, method of Lagrange multipliers, multiple integrals, line and surface integrals, Green’s theorem, Stokes’ theorem and divergence theorem.
本科教授多元微積分的基本概念與方法，以及其在工程上的應用。內容包括：多元函數、曲線與曲面、偏導數、泰勒公式、拉格朗日乘子法、多重積分、曲線與曲面積分、格林定理、斯托克定理和散度定理。
ENGG2440/ESTR2004 Discrete Mathematics for Engineers 離散數學的工程應用
Set theory, functions, relations, combinatorics, graph theory, algebraic systems, propositional and predicate logic. Not for students who have taken CSCI2110, ENGG2460, ESTR2004 or ESTR2010.
集（合）論、函數、關係（式）、組合學、圖論、代數系（統）、命題及謂詞邏輯
ENGG2760/ESTR2018 Probability for Engineers 概率及其工程應用
A first course in the fundamentals of probability theory and their applications in engineering. Topics include sample space and events, counting, axioms of probability, conditional probability, independence of events, discrete and continuous distributions, random variables, joint distributions, and limit theorems.
本科教授概率論基礎及其在不同工程領域上的應用。內容包括：樣本空間與隨機事件、計數法則、概率公理、條件概率、獨立事件、離散與連續分佈、隨機變量、聯合分佈和極限定理。
MATH1510 Calculus for Engineers 微積分的工程應用

This course is designed for engineering students who need to acquire skills in calculus as a crash introduction to the mathematics used in engineering. The course emphasizes on the technique of computation without theoretical discussion. Students are expected to have mathematics background equivalent to HKDSE with Extended Module I or II.
本科專為工程學院學生而設。簡介微積分技巧及其在工程中的應用。本科強調計算技巧，而非嚴格理論。學生要具備等同於香港中學文憑考試數學延伸部分單元一或二之數學基礎

ENGG1110/ESTR1002 Problem Solving By Programming 應用程式設計

This is a software project course. Students will learn fundamental programming concepts. They will choose project(s) from the engineering disciplines. Through the project(s), students will acquire the skills to define problems and specifications, to perform modelling and simulation, to develop system prototypes, to carry out verification, validation, and performance analysis. Not for students who have taken CSCI1030 or 1110 or 1120 or 1130 or 1510 or 1520 or 1530 or 1540 or ESTR1002 or 1100 or 1102.
本科通過軟件項目的設計和實踐來介紹工程學的基本概念。內容包括程式編寫概念。學生從各工程學科問題中選擇工程項目。通過實踐，學生獲得多種技能，包括：項目的議題及草擬規格、模型的設立和問題的模擬、原型的開發、核實、確證和表現的分析。

CSCI1120/CSCI1130/ESTR1100/ESTR1102 Introduction to Computing Using C++ 計算導論(C++語言)
Computer-oriented problem-solving methods and algorithm development; object oriented programming concepts; concepts of abstract data types; simple data structures; illustrative applications. The C++ programming language will be used. Not for students who have taken ESTR1100 or 1102 or CSCI1020 or 1110 or 1130 or 1510 or 1520 or 1530 or 1540. Equivalent to CSCI1111 offered in 2007-08 and before.
本科介紹面向計算機的問題求解方法及算法開發；面向對象程序設計概念；抽象數據類型概念；簡單數據結構；應用示例。本科使用高級程序設計語言”C++”講授。
CSCI2040 Introduction to Python Python程序語言導論

This course aims to provide an intensive hands-on introduction to the Python scripting language. Topics include the basic Python language syntax, variable declaration, basic operators, programme flow and control, defining and using functions, file and operating system interface. Specific key features of the Python scripting language such as object-oriented support, functional programming support, lambda function, list comprehension, high level dynamic data types, embedding within applications, module creation etc. will be highlighted. Special topics include using Python for web/data access, animation, as well as using Python to develop a web crawler. Not for students who have taken CSCI1040.
本科旨在密集介紹高階程序設計語言 Python 。內容包括基本高階程序設計語言Python 的語法、變數申明、基本運算符、程序編寫流程及控制、函數定義及應用、文件及操作系統接口。本科亦會介紹高階程序設計語言 Python 的特性，例如面向對象支援方法、函數式編程、lambda函數、列表解析、高階動態資料型式，嵌入於應用程式、創建模塊等。特別專題包括使用Python在網絡/數據訪問，動畫，以及使用Python開發網絡爬蟲。

CSCI2120 Introduction to Software Engineering 軟件工程導論
This course aims to introduce students to software engineering concepts. Software life cycles and processes: requirements analysis and specifications; design techniques, functional design, object oriented design; implementation methodology, software testing and maintenance; application of CASE tools; documentation. Software Engineering laboratory: a series of exercises to practise the principles of software engineering. Not for students who have taken CSCI3100 or IERG3080 or ENGG3820. Prerequisite: CSCI1110 or 1120 or 1130 or 1510 or 1520 or 1530 or 1540 or ESTR1100 or 1102 or (MATH2210 and 2220) or PHYS2351 or its equivalent.
本科旨在介紹軟件工程中的一些基本概念，包括軟件生命周期和過程，需求分析和規範，設計方法，功能設計，面向物件設計，實施方法，軟件測試和維護，CASE 工具的應用以及軟件文檔等。軟件工程實驗室：通過一系列練習來實踐軟件工程中的這些基本原理。
CSCI3150/ESTR3102 Introduction to Operating Systems 操作系統導論

Principles of operating systems: process management, memory management, file system, protection and security. Design and implementation methodology, performance evaluation. Case studies. Concurrent Programming. Prerequisite: ESTR2102 or CSCI2100 or 2520. For senior-year entrants, the prerequisite will be waived. Not for students who have taken ESTR3102.
操作系統原理：進程管理、存儲器管理、文件系統、保護及保密性。設計及實踐之方法論，性能評價。實例研究。並行程序設計。

CSCI3160/ESTR3104 Design and Analysis of Algorithms 算法設計及分析
Basics of algorithm analysis: correctness and time complexity. Techniques for designing efficient algorithms: greedy method, divide and conquer, and dynamic programming. Fundamental graph algorithms: graph traversals, minimum spanning trees and shortest paths. Introduction to complexity theory: polynomial-time reductions and NP-completeness. Not for students who have taken ESTR3104 or CSCI3190; Pre-requisites: CSCI2100 or CSCI2520 or ESTR2102, and CSCI2110 or ENGG2440 or ESTR2004.
算法分析基礎：正確性與時間複雜性。快速算法設計技術：貪婪策略、分治策略、動態規劃。圖算法基礎：圖搜索、最小生成樹、最短路徑。複雜性理論入門：多項式時間變換、NP 完全理論性。
CSCI4430/IERG3310/ESTR3310/ESTR4120 Data Communication and Computer Networks /Computer Networks 數據通信及計算機網絡 /計算機網絡

CSCI4430This course aims to introduce fundamental concepts and technologies in computer networking. The course adopts a top-down approach introducing the TCP/IP networking stack. The design of the contemporary communication applications will be studied. The fundamental concepts in implementing the reliable transport protocols, such as TCP, will be taught in this course. Design issues of TCP, such as the sliding window protocol and the congestion control, will also be included. This course will also focus on the IP network and the routing algorithms used in the Internet. Last, the design issues in the data link layer (e.g., Ethernet), including the medium access control, will be introduced. Prerequisite: CENG3150 or CSCI3150 or ESTR3102. 2. Not for students who have taken IERG3310.
CSCI4430本科旨在介紹有關電腦網絡的基礎概念與技術。本科採用由上而下的手法來介紹TCP/IP 協議。本科介紹現代的通訊應用的設計。然後，介紹以實踐可靠的通訊協議的基本概念，如 TCP 的實踐。同時，本科亦包括了 TCP 的設計課題，如滑窗協議及壅塞控制。本科同時亦集中討論IP網路與互聯網中使用的路由演算法。最後，本科介紹數據鏈路層（如乙太網）的課題，包括媒體存取控制。

IERG3310 OSI reference model. Overview of TCP/IP. Local area networks and wide area networks. Network layer and protocols. Transport layer and protocols. Examples of application layer protocols such as HTTP. Network security: firewall, SSL, and private and public keys encryption systems. One term project on client-server programming to create a web server and proxy. Not for students who have taken CSCI4430.

IERG3310 開放式系統互連（OSI）參考模型。TCP/IP 概論。局域網及廣域網。網絡層及其協議。傳輸層及其協議。應用層協議實例：HTTP 。網絡安全：防火墻、加密套接字協議層（SSL）及私鑰和公鑰加密系統。實用項目（學期內完成）是通過客戶 － 服務器編程，實現網絡服務器和代理服務器的功能。

ECON2011 Basic Microeconomics 基本個體經濟學
This course covers basic concepts in microeconomic theory. Major topics include: consumer preference and decision-making, demand theory and applications, theory of the firm, perfect competition in partial equilibrium, monopoly, oligopoly, basic game theory, general competitive equilibrium, welfare economics and market failure.
本科講授個體經濟概念，主題包括：消費者偏好及決策、需求理論及應用、企業理論、局部均衡中之完全競爭、壟斷、寡頭壟斷、基本博奕論、一般競爭性均衡、福利經濟學及市場失靈。
FINA2310 Fundamentals of Business Finance 金融財務基礎

This course introduces non-business students to the foundations for finance. It identifies and provides a framework for analysing major financial decisions of a firm. Issues addressed include valuation, investment decision-making, analysis of risk, financial planning, dividend policy, working capital management and the financing mix for the firm. This course will also provide the economics and accounting background necessary for fundamental financial analysis. Not for students who have taken ECON3540, FINA2010 or FINA2110.
本科旨在向商科以外的學生介紹基礎的金融與財務知識。涉及的課題包括估值、投資決策的形成、風險分析、財務計劃、股息政策、營運資金管理及資本結構。同時亦會介紹對金融與財務分析基礎有關的經濟及會計知識。

FTEC2001 FinTech Regulation and Legal Policy 金融科技的監管與法律政策

This course examines the legal and regulatory aspects of Fintech, particularly in the context of Hong Kong and Mainland China, to set the foundation for a practical understanding of the legal environment in which Fintech develops and evolves. The topics covered in this course include, amongst others, the general regulatory framework for the financial markets, the specific policy for Fintech, the regulatory approach towards Fintech, equity crowdfunding regime, P2P Lending rules, robot advisory services, electronic and alternative payment systems, digital currency, program trading, contract law basics and Regtech. Given the nature of the course, a comparative approach will be adopted to examining the topics covered. The course is essential for students intending to pursue a career in the Fintech industry.
本課程將探討金融科技在香港和中國大陸的背景下的法律問題， 為學生實際了解金融科技發展和演變的法律環境奠定基礎。 本課程涵蓋的內容包括金融市場的一般監管框架，金融科技的具體政策，金融科技的監管方法，股權眾籌制度，P2P貸款規則，機器人諮詢服務，電子支付系統，替代支付系統，數字貨幣和程序交易中的法律問題, 合約法基礎和金融監管科技等。 鑑於課程的性質，將採用比較的方法來研究所涉及的專題。該課程對於打算從事金融科技行業的學生至關重要。

ACCT2111 Introductory Financial Accounting 財務會計導論

This course is designed to provide students with a comprehensive understanding of financial accounting principles, practices and its underlying theories. In this course, we will emphasize on basic financial accounting concepts and principles, and discuss how to measure a company’s net income, assets, liabilities and shareholders’ equity using Generally Accepted Accounting Principles (GAAP).
本科講授財務會計的原理及實務。主要課題包括：財務會計的基本概念和原理，及利用公認會計準則（GAAP）計算企業損益、資產、負債及股東權益。

ECON2021 Basic Macroeconomics 基本總體經濟學

This course covers basic concepts in macroeconomic theory. Major topics include: national income accounting, consumption and investment theories, demand and supply of money, unemployment and inflation, fiscal and monetary policies, balance of payments and exchange rate systems.
本科講授總體經濟概念，主題包括：國民所得核算、消費與投資理論、貨幣供求、失業與通貨膨脹、財政與貨幣政策、國際收支平衡以及匯率制度。

FINA3020 International Finance 國際金融

This course aims to analyse international monetary relations and problems. Major areas of discussion include basic concepts and analysis of the balance of payments, the foreign exchange market, determination of spot and forward exchange rates, international capital flows, the payments adjustment mechanism, international monetary problems and arrangements, and international debt and its development. Prerequisite: FINA2010 or 2011 or 2110 or 2310 or permission from instructor.
本科旨在分析國際貨幣關係與問題。討論範圍主要包括國際收支之概念及分析、外匯市場、現貨及期貨匯率之決定、國際資金流動、收支調整機能、國際貨幣問題與調解及國際債務及其發展。

FINA3030 Management of Financial Institutions 金融機構管理

This course discusses the economic and environmental problems in the acquisition and use of funds by financial institutions. The emphasis is on the fundamental principles underlying the organization and management of a commercial bank. Considerations are given to recent developments in banking regulations, electronic banking, asset and liability management, various major policy areas and their interrelationships.
本科討論金融機構在吸收與運用資金時應考慮之經濟與環境問題。內容著重討論商業銀行組織與管理之基本原理。考慮範圍包括近年銀行法例之發展、銀行電腦化、資產與負債管理及銀行主要業務政策之制定及其相互之影響。

FINA3070 Corporate Finance: Theory and Practice 公司財務：理論與實務

This course builds on the concepts introduced in FINA2010 and aims to provide students with advanced study of corporate investment and financing decisions. Major topics covered include working capital management, capital budgeting, capital structure, sources of financing, dividend policy, leasing, and mergers and acquisitions. 1. Prerequisite: FINA2010 or 2011 or 2110 or 2310 or permission from instructor. 2. Not for students who have taken ECON3540.
本科以FINA2010 所介紹之觀念為基礎，旨在為學生提供對公司投資及融資決策較深入之探討。主要內容包括營運資金管理、資本預算、資本結構、融資來源、股息政策、租賃及合併與收購等。

FINA3210 Risk Management and Insurance 風險管理與保險

This course covers risk management concepts; risk identification and measurement; property, net income, and liability loss exposures; analysis of life, property and liability insurance contracts; methods and problems of insurance pricing; and insurance regulation and public policy. In this course, insurance is treated as a major tool of risk management. Prerequisite: FINA2010 or 2011 or 2110 or 2310 or permission from instructor.
本科內容包括風險管理之概念；風險之鑒別與衡量；產業、利益、與責任性損失範圍；保險收費之擬定方法與問題；以及政府對保險業所訂之法例與政策等。本科將保險學之探討列為風險管理之主要工具。

FINA4010 Security Analysis 證券分析

This course covers the basic issues and principles of fundamental analysis, which deals with the valuation of a firm’s equity shares and debt by using macroeconomic and industry information, financial statements, financial forecasting, financial modeling, discounted cash flow method of equity valuation, and development of techniques for valuing equity and fixed income securities research. Prerequisite: FINA2010 or 2011 or 2110 or 2310 or permission from instructor.
本科旨在介紹學生一些概念性的背景知識和分析方法，使其能夠認識、評估和運用資訊對金融證券進行基本分析。重點放在結合整體經濟及産業資訊、財務報表、財務預測、金融建模、以及定價概念、商業政策和財務分析，以進行股權及固定收益證券估值分析。

FTEC2101/ESTR2520 Optimization Methods 優化方法

This course introduces the essentials of optimization methods, including models, solution methods, and programming techniques. Topics cover linear programming, integer linear programming, nonlinear programming, and convex programming. It will highlight applications of these methods in Fintech, such as asset allocation, portfolio management, and data analysis.
本課程介紹優化方法的基礎知識，包括模型，解決方法和編程技術。 主題涵蓋線性規劃，整數線性規劃，非線性規劃和凸規劃。 課程將重點介紹這些方法在金融科技中的應用，如資產配置，投資組合管理和數據分析。

SEEM2520 Fundamentals in Financial Engineering 金融工程學基礎

Overview of financial markets for securities, foreign exchange, options and futures; special emphasis on understanding of the market characteristics; interpretation of financial statements of an organization in terms of liquidity, solvency, profitability, efficiency and growth.
證券、外匯、期權與期貨市場的概況，理解市場的特徵為本科的重點，從財務報告中了解機構的流動性、償債力、盈利力、效率及增長。

SEEM3590/ESTR3509 Investment Science 投資科學

Basic theory of interests, fixed income securities, the term structure of interest rates, valuation of a firm, decision making under uncertainty, mean-variance portfolio theory, capital asset pricing model, models and data, basics of forward and futures contracts, basic options theory. Not for students who have taken ESTR3509.
利率論的基礎，固定收益的證券，利率的年期結構，公司的估值，不確定環境下的決策，均值方差組合理論，資本財產定價模型，模型及數據，遠期及期貨合約的基礎，期權的基本理論。

FTEC4002 Behavioral Analytics 定量行為分析

ehavioral analytics is a recent advancement that reveals customer behaviors. In this course, we will focus on (i) how to use optimization techniques to design survey questions and to collect data that are relevant to customer behaviors, (ii) theories of customer behaviors, especially those under risk, (iii) how to use data mining techniques to reveal customer behaviors, and (iv) psychological biases in customer behaviors and their impact on financial and business decisions.
定量行為分析是一門通過定量方法刻劃顧客行為的新興學科。 本課程將重點講述（i）如何使用優化技術來設計調查問卷並收集與顧客行為的相關數據，（ii）建立顧客的行為理論，特別是他們面臨風險選擇下的行為， （iii）如何使用數據挖掘技術來刻劃顧客行為，以及（iv）顧客行為中顯現的心理偏差及其對金融和商業決策的影響。

MKTG4120 Quantitative Marketing 數量巿場學

Due to the recent advances in computer technology, marketers can now collect huge amounts of customer data and analyse them to support better decisions. The course focus is to apply popular multivariate statistical methods in marketing research. The course content mainly includes stochastic brand choice models, customer segmentation models, product positioning models. SAS programming will be introduced to implement the quantitative models. Pre-requisities: MKTG2010 and MKTG3010
隨著電腦科技的進步，營銷人員能搜集更多數據，並分析及應用在營銷決策。這科目的重點是應用多變量統計方法，以解決市場研究的問題。科目內容包括品牌選擇模型、顧客細分模型及產品定位模型。本科利用SAS軟件/語言來實現各種定量模型。

SEEM3410 System Simulation 系統模擬

System concept and mathematical models. Model building: parameter estimation and data analysis. Elementary queuing theory and applications: M/M/S models. Introduction to simulation and simulation language. Principles of discrete event simulation. Random number generators and output analysis. Optimization via simulation. Applications to production and manufacturing systems. Prerequisites: SEEM2430 or ENGG2430 or ENGG2450 or ESTR2002 or ESTR2005 or with the approval of the course instructor.
系統概念和數學模型。模型之建立：參數估計和數據分析。基本排隊模型的理論及應用：M/M/S 模型。模擬和模擬語言簡介。離散事件系統模擬原則。隨機數產生器及輸出分析。模擬優化。在生產製造系統中的應用。

SEEM3570/ESTR3508 Stochastic Models 隨機模型

Review of basic probability. Probabilistic dynamic programming. Stochastic processes and Markov chains. Birth-and-death processes and queuing models. Stochastic inventory models: single and multiple periods. Forecasting and time series. Markov decision processes. Not for students who have taken ESTR3508. Prerequisite: SEEM2430 or ENGG2430 or ESTR2002 or with the approval of the course instructor.
基礎概率論回顧。概率動態規劃。隨機過程和馬氏鏈。生死過程和排隊模型。隨機庫存模型：單、多周期模型。預測及時間序列。馬氏決策過程。

SEEM3580 Risk Analysis for Financial Engineering 金融工程的風險分析

Analysis and modelling of market, credit, and operational risks in Financial Engineering. Fundamental financial instruments and derivatives: forward, futures, options, and swaps. Sources and models of market risks: interest rate, foreign exchange rate, equity prices, and commodity prices. Major credit scoring and rating models: Z-score, Logit, and Merton. Major commercial applications and systems, KMV and CreditMetrics. Different approaches to measure Value at Risk (VaR): historical, parametric, and Monte Carlo.
金融工程的市場，信貸，與操作風險的分析及建模。基本金融工具與衍生商品：遠期，期貨，期權，及交換。市場風險的主要來源以及評估模型：利率，匯率，證券，及期貨價格的波動。主要評級以及信貸風險分析模型：Z-score ， Logit 及 Merton 。商業系統如 KMV 和 CreditMetrics 。不同的在險值計算方法，包括：歷史、參數及 Monte Carlo 。

ENGG2780/ESTR2020 Statistics for Engineers 統計及其工程應用

A first course in the fundamentals of statistics and their applications in engineering. Topics include populations and samples, point estimation, confidence intervals, hypothesis testing, and basics of linear regression.
本科教授統計學基礎及其在不同工程領域上的應用。內容包括：母群及樣本、點估計、區間估計、假設檢驗和線性回歸的基本概念。

FTEC4003 Data Mining for FinTech 面向金融科技的數據挖掘

This course introduces key techniques on data mining, including data preprocessing, classification, association rule mining, and clustering and outlier detection. Applications of these techniques in financial market data will be discussed with hands-on practice on data mining packages.
本課程介紹了數據挖掘的核心技術，包括：數據預處理，分類，關聯規則挖掘，聚類，以及異常點檢測。同時，結合數據挖掘軟件的實際使用討論這些技術在金融市場資數據的應用。

AIST4010/ESTR4140 Foundation of Applied Deep Learning 應用深度學習基礎

This course covers how to use deep learning techniques to resolve real-life computational problems, handling different kinds of data. We start the course by introducing the problem-solving paradigm with deep learning: data preparation, building the model, training the model, model evaluation, and hyper-parameter searching. Then, we fill in the details in the paradigm. Regarding the deep learning models, we will go from the simplest linear regression model, towards the relatively complicated models. To handle various data types, that is, the structured data, images, text, sequences, signals, and graphs, in our daily life, we would cover CNN/ResNet, RNN/LSTM, Attention, and GNN models. In addition to the above paradigms, we will also cover the commonly used techniques to handle overfitting. We would briefly go through the generative models, VAE, and GAN, at the end of this course.
本科將詳細介紹如何使用深度學習去處理並解決實際生活中遇到的各種數據類型。本科開始將首先介紹用深度學習去解決問題的流程和框架：數據預處理、構建模型、訓練模型、評估模型及超參數搜索。然後詳細介紹這個流程中的細節。深度模型部分，將從最簡單的線性模型開始介紹並逐漸增加模型的複雜度。為了處理不同的數據類型，即結構化數據、圖像、文本、序列、信號和網絡，本科將介紹CNN/ResNet, RNN/LSTM, Attention和GNN模型。除了上述流程，本科還會詳細介紹如何處理深度學習中的過擬合問題。最後，本科將簡單介紹生成模型：VAE和GAN。

CSCI3320 Fundamentals of Machine Learning 機器學習之基礎課程

The first part introduces basic methods, including minimum error versus maximum likelihood, parametric versus nonparametric estimation, linear regression, factor analysis, Fisher analysis, singular value decomposition, clustering analysis, Gaussian Mixture, EM algorithm, spectral clustering, nonnegative matrix factorization. The second part provides an introduction on small sample size learning, consisting of model selection criteria, RPCL learning, automatic model selection during learning, regularization and sparse learning. Prerequisite: ENGG2040 or ENGG2430 or ESTR2002.
第一部分介紹基本方法，包括最小誤差與最大似然、參數與非參數估計、線性回歸分析、因數分析、費歇判別分析、奇異值分解、聚類分析、高斯混合、EM 演算法、譜聚類、非負矩陣分解。第二部分簡介有限樣本學習，包括模型選擇準則、RPCL 學習、學習過程中自動模型選擇、規則化與稀疏學習。

SEEM4730/ESTR4508 Statistics Modeling and Analysis in Financial Engineering 金融工程中的統計模型與分析

Financial data are undoubtedly rich from stock markets and many websites and sources such as Bloomberg and Reuters. This course studies empirical research methods in financial engineering, i.e., deriving intelligence from data through data analysis and statistical inference. In particular, this course addresses important issues of a statistical nature such as: use of different financial market data models, estimation of model parameters, simplification of models, and elaboration of models. The key objective of this course is to address how the prices of stocks and other financial assets behave. Not for students who have taken ESTR4508.
毫無疑問，金融數據非常豐富。特別是近年來，各類網站資源（比如彭博、路透）提供的股票價格等金融數據愈來愈快捷。本科旨在學習實證分析方法在金融工程中的應用，如何運用概率統計推斷方法對數據進行有效分析。特別是本科要回答如下統計意義下的問題：各類金融市場的數據模型，模型的參數估計，模型的簡化和模型的精確化等。本科的主要目的就是要理解與認識股票以及其它金融資產的價格的變動。

CSCI2100/ESTR2102 Data Structures 數據結構

The concept of abstract data types and the advantages of data abstraction are introduced. Various commonly used abstract data types including vector, list, stack, queue, tree, and set and their implementations using different data structures (array, pointer based structures, linked list, 2-3 tree, B-tree, etc.) will be discussed. Sample applications such as searching, sorting, etc., will also be used to illustrate the use of data abstraction in computer programming. Analysis of the performance of searching and sorting algorithms. Application of data structure principles. Not for students who have taken ESTR2102 or CSCI2520; Pre-requisite: CSCI1110 or 1120 or 1130 or 1510 or 1520 or 1530 or 1540 or ENGG1110 or ESTR1100 or ESTR1102 or ESTR1002 or its equivalent. For senior-year entrants, the prerequisite will be waived. 本科介紹抽象數據類型之概念及數據抽象化的優點。並討論多種常用的抽象數據類型，包括向量、表格、堆棧、隊列、樹形；集（合）和利用不同的數據結構（例如：陣列、指示字為基的結構、連接表、2-3 樹形、B 樹形等）作出的實踐。更以實例（例如：檢索、排序等）來說明數據抽象化在計算機程序設計上的應用。並討論檢索與排序算法及數據結構之應用。

CSCI4130/IERG4130/ESTR4306 Introduction to Cyber Security 網際安全概論

Cyber Security is an important topic in modern information and communication technology. This course introduces students to major areas of Cyber Security, including introductions to cryptography, network security, computer security, and web security. Advisory: Basic knowledge on Computer Networks are suggested.
網際安全是一個重要的課題在現代信息和通信技術。本科向學生介紹網際安全的主要領域，包括介紹密碼學，網絡安全，計算機安全和網頁安全。 參考意見: 選課者建議具備計算機網絡的基本知識。

SEEM3550/ESTR3506 Fundamentals in Information Systems 訊息系統工程概念

Basic elements of information systems, their concepts and interrelations. Database systems: database models, relational database, database application programming. Information retrieval: models, indexing, performance evaluation. Expert systems: knowledge and data engineering, expert system shell, application studies. Not for students who have taken ESTR3506.
訊息系統的基本要素、其概念及相互關係。數據庫系統：數據庫模型、關係數據基本概念、數據庫應用編程。訊息檢索系統：訊息檢索模型、索引構造、性能評估。專家系統：知識與數據工程、專家系統外殼、應用實例。

FTEC4001 Advanced Database Technologies 高級數據庫技術

To support high-speed online payments, one important issue is efficiency and another important issue is reliability for millions of payments to be transferred among accounts. This course introduces the advanced topics in database systems. The topics include query processing and optimization, transaction management, concurrency control, recovery systems, parallel databases, and distributed database systems.
在高速線上支付中，為支持數以百萬計的帳戶間交易，效率與可靠性是兩個重要的因素。本課程介紹了關於數據庫系統的高級主題，包括：查詢處理及優化，事務管理，併發控制，恢復系統，並行數據庫以及分佈式數據庫。

CSCI4180 Introduction to Cloud Computing and Storage 雲端計算及存儲導論

This course introduces concepts and principles of cloud computing and storage. Subjects include: cloud computing models (SaaS, PaaS, IaaS), distributed and parallel data processing (MapReduce, Hadoop, multicore technologies), virtualization technologies (hypervisor, virtual machines, full virtualization, paravirtualization), data storage (cloud storage architectures, data centers, data deduplication), security/privacy issues, and case studies of real-world cloud services (Amazon EC2, Windows Azure). This course emphasizes applied methodologies of using cloud computing and storage for solving practical engineering problems. Pre-requisite: CSCI3150 or CENG3150 or ESTR3102.
本科介紹雲端計算及存儲的概念和原則。內容包括：雲端計算模式（SaaS、PaaS、IaaS），分佈式和並行數據處理（MapReduce、Hadoop、多核心技術），虛擬化技術（hypervisor、虛擬機、完全虛擬化、半虛擬化），數據存儲（雲端存儲架構、數據中心、重複數據刪除），安全/隱私問題和現實世界中雲端服務的案例研究（Amazon EC2、Windows Azure）。本科著重利用雲端計算及存儲的應用方法以解決實際工程問題。

CSCI4160/ESTR4104 Distributed and Parallel Computing 分佈式及並行式計算

This course introduces concepts, models, and implementations related to distributed and parallel computing. Topics include parallel and distributed programming, system architectures, synchronization, and concurrency control techniques.
本科旨在介紹關於分佈式及並行式計算之概念、模型及實踐。專題包括：並行式與分佈式系統之結構、並行語言、同步及並行控制技術。

IERG4080/ESTR4312 Building Scalable Internet-based Services 搭建可擴展的互聯網服務

Mobile devices has greatly increased the demand of Internet-based services. Large-scale online services such as Pinterest and Instagram must be designed in a way such that they can be scaled up and scaled out in a rapid and seamless manner. This course will teach students how to build scalable online services and applications. In particular, the design principles and engineering considerations for different core components, including the front-end system, the load-balancer, performance monitoring, content-delivery networking, fault-tolerant mega data store, distributed messaging services, backend big data processing/ analytics will be discussed. As a course project, the students will prototype a scalable Internet service by leveraging industrial-strength component offerings from leading infrastructure and platform service providers. Advisory note: Students are expected to have background in object oriented programming. Pre-requisite: IERG3080. Not for students who have taken ESTR4312.
近年移動設備的普及大大提升了對互聯網服務的需求。設計如Pinterest及Instagram等大規模線上服務的架構時，必須考慮如何令系統能夠快速擴展。本科旨在教授學生如何搭建可擴展的線上服務與應用。本科將會討論設計原理，以及對可擴展互聯網服務的不同核心組件（包括前端系統，負載均衡器，性能監測，內容分發網絡，數據差錯容忍存儲，分佈式消息服務，後端大數據處理與分析等等）的工程考量。科目項目將會要求學生利用現成的開源或業界方案，加上科目中介紹的各種方法，實現一個可擴展的互聯網服務。參考意見: 選科者須具備面向對象編程的知識。

IERG4210 Web Programming and Security 網頁編程及網頁安全

The web programming paradigm is gaining importance. Security is among its central issues. In this course, students use programming languages such as HTML, CSS, Javascript, PHP, and the mysql database technology, to develop interactive websites with emersive user interface/ user experience. Students will also learn major web security threats and secure web programming do’s and dont’s. Projects may be used to enhance learning.
目前，網頁編程規範變得越來越重要，而安全性則是網頁編程規範的核心。在本科中，學生將使用 HTML, CSS, Javascript, PHP 等編程語言，以及 SQL 數據庫技術，開發一個具有良好用戶介面和用戶體驗的交互式網站。學生還將瞭解主要的網頁攻擊方式，以及如何在網頁編程中避免這些攻擊。本科還將設置課程大作業幫助學生加深對本科內容的理解。

FTEC3001 Financial Innovation & Structured Products 金融創新和結構性產品

The course of Financial Innovation and Structured Products provides a quantitative introduction to derivative markets. In it, we will focus on (i) the fundamental mechanics of futures, swaps and option markets, (ii) risk neutral evaluation theory of asset pricing, (iii) numerical procedures related to derivatives evaluation and risk managements, (iv) the principle of financial engineering and structured product design and their applications, and (v) financial crisis and regulation.
本課程提供了對衍生品市場的定量介紹。重點講述（i）期貨，掉期和期權市場的基本機制，（ii）資產定價的風險中性定價理論，（iii）與衍生品定價和風險管理相關的數值方法，（iv） 金融工程和結構性產品的設計原理及其應用，以及（v）金融危機和監管。

FTEC3002 Introduction to Financial Infrastructures 金融基建概論

This course provides an introduction to financial infrastructures. Topics include trading venues and platforms, securities settlement systems, payment systems, system links that facilitate cross-border transactions, central counterparties and clearance, cybersecurity infrastructure for financial services industry, infrastructure-related systemic risk and its impact on monetary and financial stability.
本課程介紹金融市場相關的基礎設施，內容包括交易場所和平臺，證券結算系統，支付系統，跨境交易的系統連接，共同對手方和中央清算，以及基礎設施引起的系統性風險和其對貨幣和金融穩定性的影響。

FTEC4008 Natural Language Processing for FinTech 面向金融科技的自然語言處理

The course aims at equipping students with an overview of latest natural language processing (NLP) technologies that have been increasingly adopted in finance sector. The course will introduce basic concepts of NLP and the advanced developments based on machine learning, especially deep learning. The topics of word representations, sequence modeling, large language models, and conversational AI will be further explored. Based on the introduced foundation in NLP, multiple financial applications will be introduced to illustrate how NLP techniques, e.g., text mining, sentiment analysis, conversational AI and large language models, can increase productivity in various scenarios, including general financial data processing practice and specific RegTech and InsurTech use cases. Students will have ample opportunities to apply the learned techniques in hands-on implementation on course projects.
在金融領域，越來越多的產品與服務採用先進的自然語言處理（natural language processing，NLP）技術以提高生產力、優化服務質素。本科目旨在讓學生深入了解NLP基礎知識和先進技術及其金融科技應用。 本科目將介紹NLP的基本知識和理論，包括詞表征、句法結構、序列建模、語言模型和對話系統，以及基於機器學習，尤其是深度學習，的最新技術進展，包括基礎模型、大語言模型和對話式人工智能。 基於這些NLP理論基礎和技術背景，本科目將通過金融科技應用實例以展示 NLP 技術（例如文本挖掘、情感分析、對話式人工智能、大語言模型生成）在多種場景下如何提高生產力與優化服務質素，包括通用的金融數據分析方法以及特定的監管科技（RegTech）和保險科技（InsurTech）實際案例。 在本科目中，學生將有充足的機會將學到的理論與技術應用於科目項目實踐中以獲得實戰經驗。學生亦會對NLP技術的能力邊界和局限性有深入理解，從而為更好地在金融科技實踐中應用NLP技術提供基礎。

FTEC4005 Financial Informatics 金融信息學

This course introduces basic concepts, models, techniques, and applications on financial data analytics. Topics include processing and analytical techniques for data streams; processing and searching high-dimensional data; big graph analysis; Web mining; recommendation systems for Web applications. The applications may involve financial data processing and analysis, time series, portfolio management, social networks, recommender systems, and so on.
本課程介紹了有關金融數據分析的基本概念、模型、技術和應用。主要問題包括：數據流的處理與分析；高維數據的處理與查詢；大規模圖數據分析；網絡挖掘；面向網絡應用的推薦系統。相關應用包括：金融數據處理與分析，時間序列、組合資產管理，社交網絡，推薦系統等。

FTEC4006 Internet Finance 互聯網金融

This course provides students with the fundamentals in the operations and management of Internet finance. It will cover overall applications of Internet-based technologies such as mobile payments, social network, search engines, cloud computing, and big data on the financial sector. Specific topics include third-party payments, Internet currency, P2P lending, crowdfunding, and the use of big data in financial services. The course adopts case studies as the major means of teaching and learning..
本課程教授學生互聯網金融運營和管理的基礎知識，著重於移動支付，社交網絡，搜尋引擎，雲計算，以及大數據等的基於互聯網的技術的金融應用。 內容包括協力廠商支付，互聯網貨幣，P2P借貸，互聯網眾籌，和大數據在金融服務業中的應用等。 本課程將採用案例分析作為主要的教學手段。

FTEC4007 Introduction to Blockchain and Distributed Ledger Technology 區塊鏈及分佈式分類帳技術介绍

The course will cover the technical aspects of cryptocurrencies, blockchain technologies, distributed ledger technology and their applications. Students will learn how these systems work and how to develop secure software application that interacts with the Bitcoin network and other cryptocurrencies.

SEEM3450/ESTR3502 Engineering Innovation and Entrepreneurship 工程創新和企業開發

Factors that drive continuous creative product innovation. Study of processes of creating, assessing and pursuing product opportunities. Evaluation of new product ideas and risk assessment of commercialization. Product development strategies in industrial marketing. Understanding the behaviour of buyer. Formulation and implementation of innovative marketing strategy and business plan. Not for students who have taken ESTR3502.
延續產品創新之動機要素。創新、評核及尋求產品機會之過程研究。新產品概念之評審及商品化之風險評估。工業市場的產品開發策略。買方行為探討。創新市場策略之釐訂及實施和商業計劃。

FTEC2602 Financial Technology Practicum 金融科技實務

Industrial and professional workshops or seminars related to Financial Technology practicum.
與金融科技實務相關的工業和專業工作坊或講座

ENGG1820 Engineering Internship 工程實習

The objective of the course is to enable students to have a basic understanding of the practical aspects of the engineering profession. Prior to the enrolment of this course, students must have completed not less than 8 weeks of full-time internship approved by the Faculty of Engineering. To be qualified for award of the subject credit, the student must submit a report, within the semester of enrolment, summarizing what he or she has done and learnt during the internship, together with a testimonial from the corresponding employer. Pass or fail of the course will be determined by the professor-in-charge, based on the report and the testimonial submitted. Student may look for internship opportunities at the Placement and Internship Program (PIP) website administered by Centre for Innovation and Technology of the Faculty, or from any other sources available to him or her. Students are recommended to seek professor-in-charge’s comment on internship undertaken before enrolling in the course. Work-Study, the 12-month internship program organized by the Faculty, is a valid internship satisfying the requirements of ENGG1820. Advisory: For year 2 or above Engineering Majors students. (new curriculum)
本科目標是讓學生對工程專業的實際工作有基本的認識。學生選修本科前，必須先完成不少於八星期全職、獲工程學院認可的實習工作。為取得本科學分，學生需要在修讀本科的學期內提交僱主評語和實習報告，說明實習內容及所學知識，負責本科的教授會根據報告和僱主評語的文本來決定學生是否及格。學生可以在工程學院創新科技中心管理的「實習與就業」網頁尋找實習工作，其他途逕覓得實習機會亦可以考慮。學生最好在報讀本科前詢問老師對有關實習工作的意見。工學院主辦為期十二個月的「工讀計劃」，是符合本科要求的實習計劃。 參考意見： 只供工程學院主修生於第二修業學年或以上修讀 。(新學制)

ADMISSION CRITERIA


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JUPAS Admissions

Secondary school students taking Hong Kong Diploma of Secondary School Examination (HKDSE) should apply for admission through the Joint University Programmes Admissions System (JUPAS). The JUPAS code of the B.Eng. in Financial Technology Programme is “JS4428”.

Application Requirements (applicable to HKDSE applicants for 2024-25 onwards)

Admission is based on the Best 5 HKDSE subject results with subject weighting. For details of subject weighting, please refer to the table below.

Minimum Admission RequirementSubjectMinimum GradeSubject Weighting
Core SubjectsEnglish Language31.25
Chinese Language31.25
Mathematics41.75
Citizenship and Social DevelopmentAttained (A)Will not be used in admission scores calculation
Two Elective SubjectsAny two subjects3#

# The Financial Technology Programme has no specified elective. The preferred subjects include Business Accounting and Financial Studies, Information and Communication Technology, Economics, Physics, Chemistry, Biology, Combined Science, Mathematics Extended Module 1 or 2.

A subject weighting of 1.5 is given to the above preferred subjects, except that 1.75 is given to Mathematics Extended Module 1 or 2.  A subject weighting of 1.0 is given to any other subjects.

In addition to the requirements above, bonus points will be awarded to the 6th and 7th subjects, if any.

Grade Point Conversion Table
HKDSE Level5**5*54321
Grade Point8.575.54321

Non-JUPAS Year-1 Admissions

The programme accepts and welcomes Non-JUPAS Year 1 applicants..   Please refer to the website of the Office of Admissions and Financial Aid at https://admission.cuhk.edu.hk/ for the admission requirements of qualifications other than HKDSE.  The Programme does not have specific Non-JUPAS programme requirements, though preference will be given to students with strong performance in preferred subjects.   For the preferred subjects, please make reference to the HKDSE elective subjects marked with # above.   Due to the diversity of non-JUPAS qualifications, applications will be assessed on individual merit.

STUDY SCHEMES


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(Study Schemes – English)

Programme Title:           Financial Technology (FTEC)
Study Scheme Applicable to students admitted in 2024-25

Major Programme Requirement
Students are required to complete a minimum of 75 units of courses as follows:
Units
1.Faculty Package:
ENGG1110/ESTR1002, ENGG1120/ESTR1005, ENGG1130/ ESTR1006		9
2.FinTech Foundation Courses:
CSCI1120/CSCI1130/ESTR1100/ESTR1102, ENGG2440/ESTR2004, ENGG2760/ESTR2018, ENGG2780/ESTR2020, MATH1510		13
3.Required Courses:
(a)CSCI2100/ESTR2102, CSCI4130/IERG4130/ESTR4306, ECON2011, FINA2310, FTEC2101 /ESTR2520, FTEC3001, FTEC3002, SEEM2520, SEEM3550/ESTR3506, SEEM3590/ESTR3509 30
(b)Research Component Courses:
FTEC4998, FTEC4999 		6
(c)Practicum Course:
FTEC2602		1
(d)Legal Course:
FTEC2001 		2
4Elective Courses:
At least 6 units from FTEC4001, FTEC4002, FTEC4003, FTEC4008, FTEC4006, FTEC4007
Courses from at least 3 subject areas:
ACCT2111, AIST4010 / ESTR4140, CSCI2040, CSCI2120, CSCI3150 / ESTR3102, CSCI3160 / ESTR3104,CSCI3320, CSCI4160 / ESTR4104,CSCI4180 / ESTR4106, CSCI4430 /IERG3310 / ESTR3310 /ESTR4120, ECON2021, ENGG1820, FINA3020, FINA3030, FINA3070, FINA3210, FINA4010, IERG4080 / ESTR4312, IERG4210, MKTG4120, SEEM3410,SEEM3450 / ESTR3502, SEEM3570 / ESTR3508, SEEM3580, SEEM4730 / ESTR4508		14
Total: 75

Upon completion of the Bachelor of Engineering Programme in Financial Technology, students may consider to continue their studies for the second bachelor degree in Integrated Business Administration (IBBA) subject to the prescribed admission requirements.  For details, please visit to the website of the Faculty of Engineering at http://www.erg.cuhk.edu.hk/erg/ergbba

PROGRAMME REQUIREMENT


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INTERNSHIP


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PLACEMENT


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Examples of employers of our students:

  • Commercial banks (e.g, HSBC, Bank of China (HK), Dah Sing)
  • Investment banks (e.g., Goldman Sachs)
  • FinTech companies (e.g., FNZ, HKAIFT)
  • Asset management (e.g., Hex Trust)
  • Consulting (e.g., Deloitte)

OVERSEAS EXCHANGE


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Our students have participated in exchanges at various places around the globe.

  • United States and Canada: e.g., Dartmouth College, Stony Brook University, University of Washington, McGill University.
  • Europe: e.g., King’s College London, Université Catholique de Lille.
  • Asia: e.g., Nanyang Technological University, Korea University.

ACADEMIC HONESTY


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Students are required to meet the highest standard of academic honesty.  All students should learn and be aware of the following standards and guidelines:

SCHOLARSHIPS


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JUPAS applicants with excellent DSE results (best five total >=30) as well as Non-JUPAS applicants with excellent results in their qualification exams will be awarded a generous one-time scholarship.