Programme

BENG SEEM Curriculum

CURRICULUM

The curriculum of the SEEM program is designed to provide students with solid and comprehensive training in programming, mathematical modelling, entrepreneurship and management, data science, and various applications. The training is supported by an extensive list of high-quality courses, including not only courses in SEEM but also some courses in computer science and in financial technology.

ENGG1110/ ESTR1002 Problem Solving By Programming 應用程式設計
This is a computer-programming course to equip students with software knowledge and skills to solve engineering problems. Students will learn fundamental programming concepts in C, such as data representation and variables, operators and expressions, flow-control statements, functions, arrays, structures, pointer basics, input/ output handling, etc. In addition to lectures and e-learning, students will work in labs to practise solving problems and complete an engineering software project. The course will cover various problem solving methods such as incremental development, divide-and-conquer, debugging technique, finite-state machine, etc. Through practices, students will acquire skills to define problems and specifications, to perform modelling and simulation, to develop software system prototypes, to carry out verification, validation, and performance analysis.
本科為計算機編程課程,為學生提供解決工程問題的軟件知識和技能。學生將學習C語言中的基本編程概念,例如數據表示和變量,運算符和表達式,流程控制語句,函式,數組,結構,指針基礎知識,輸入/輸出處理等。除了講課和線上學習,學生將在計算實驗室實習解決問題,並完成一工程軟件項目。此科將涵蓋各種問題解決方法,如增量開發,分而治之,調試技術,有限狀態機等。通過實踐,學生將獲得多種技能,包括:議題及草擬規格、進行建模和模擬、開發軟件系統原型、進行核實、驗證和性能分析。
CSCI1120/ ESTR1100 Introduction to Computing Using C++ (計算導論(C++語言))
CSCI1120/ ESTR1100 Introduction to Computing Using C++ 計算導論(C++語言)
This course introduces the 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.
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。

CSCI1130/ ESTR1102 Introduction to Computing Using Java 計算導論(JAVA語言)
This course aims at providing students with the basic knowledge of computer programming. In particular, programming methodologies such as object-oriented programming and structured programming, and the use of abstract data types will be illustrated using high-level programming languages such as Java.
本科旨在向學生提供計算機程序設計之基礎知識,並以高級程序設計語言(如Java)講解包括面向對象程序設計和結構程序設計等之程序設計方法學及抽象數據類型之運用。

CSCI1130/ ESTR1102 Introduction to Computing Using Java (計算導論(JAVA語言))
This course aims at providing students with the basic knowledge of computer programming. In particular, programming methodologies such as object-oriented programming and structured programming, and the use of abstract data types will be illustrated using high-level programming languages such as Java.
本科旨在向學生提供計算機程序設計之基礎知識,並以高級程序設計語言(如Java)講解包括面向對象程序設計和結構程序設計等之程序設計方法學及抽象數據類型之運用。
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. Advisory note: Students are advised to have basic programming experience before taking this course.
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。 參考意見: 選科者須具備編程的知識。
CSCI2100/ ESTR2102 Data Structures (數據結構)
This course introduces the concept of abstract data types and the advantages of data abstraction. 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.
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。
CSCI4140 Open-Source Software Project Development
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。
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。
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。
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.
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。
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。
SEEM2420 Operations Research 1 (運籌學(一))
Review of linear algebra. Linear programming: simplex methods, duality and sensitivity analysis. Network flows: transportation and assignment problems, shortest paths, minimum spanning trees, network simplex method and multicommodity flows. Modelling issues in linear programming and network flows applications.
線性代數之回顧。線性規劃:單純形法,對偶及敏感分析。網絡規劃:運輸問題和分派問題,最短路線,最小支撐樹及網絡單純形法,多類商品網絡模型。線性規劃模型之應用。
SEEM3440/ ESTR3500 Operations Research II (運籌學(二))
Non-linear programming: convex sets and functions; local and global optima; Lagrange multipliers; optimality conditions for unconstrained problems; descent methods; constrained optimization; Karush-Kuhn-Tucker conditions; solution methods. Non-differentiable optimization: integer programming models; formulations; cutting-plane methods; branch-and-bound. Dynamic programming: models and formulation; Bellman’s equations; solution methods.
非線性規劃:凸集及函數;局部及整體最優;Lagrange 乘子;約束問題的最優性條件;下降方法;有約束最優化;Karush-Kuhn-Tucker 條件;解法。不可微最優化:整規劃模型;問題的歸結;切割平面法;分枝定界。動態規劃:模型及歸約, Bellman 方程;解決方法。
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.
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。
SEEM2440/ ESTR2500 Engineering Economics (工程經濟學)
Principles of engineering economy. Value and cost; cash flows. Economic analysis of alternatives, technological, social and human factors. Models involving allocation and scheduling of resources. Analytical techniques for evaluating industrial projects. Relationship between economics of technical choice and industrial productivity. Basic financial accounting concepts; accounting cycle; financial statements.
工程經濟學主要原理。價值及成本;資金流動;方案技術、社會和人力因素等問題的經濟分析。有關資源分配和調度之模型。評估工業項目之分析技術。技術經濟性和工業生產力之間的關係。基本財政會計概念;會計週期;財政報告。
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.
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。

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。學生宜在報讀本科前詢問老師對有關實習工作的意見。 工程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)
SEEM2460/ ESTR2540 Introduction to Data Science (數據科學化基礎)
This course presents an introductory roadmap into the newly emerged and rapidly evolving field of data science, with the objective of introducing the problem-solving mindset in a data-intensive context. The course projects data science as a productive synthesis of its parent disciplines, including mathematics, statistics, computing, data mining, system science and data visualization, etc. Such a productive synthesis is applicable across many fields to bring about scientific discovery through data-intensive, analytical methods. This course aims to help navigate students in taking more advanced courses in its parent disciplines to build up their expertise in data science. We cover topics including: History and impact of Data Science. Collecting Data: sources, types and categorization of data. Visualising Data: summary statistics, data display, data dictionaries, schema and graphical visualization. Analysing Data: pattern recognition, correlations and relationships, hypotheses testing, statistical significance. Investigating Data: data mining, machine learning, inference, meta-data, modeling, eliciting meaning and validation. Applicational contexts: Examples of useful applications from case studies.
這科提供基礎藍圖幫助學習數據科學化,這是嶄新及急速發展的領域,目的是學習利用科學化的方法及分析大量數據來輔助解決實用問題,訓練學生具備相關的思維。 數據科學化牽涉各學科包括數學、統計、電子計算、數據挖掘、系統科學及數據視覺化。 它可應用於各領域,透過處理及分析數據來支持科學探索與發現。這科也可增加學生對相關學科的認識,幫助他們日後修讀更深入的科目,擁有數據科學化的專業技術。 科目範圍包括: 數據科學化的歷史及影響,數據採集: 來源、種類、範疇,數據視覺化: 數據顯示、數據字典,數據架構與圖像化,數據分析:模式識別、相關性、關聯性,假設檢驗、統計顯著性測試,數據研究:數據挖掘、機器學習、推理,元數據設計,數據模型,含義抽取及驗證,實用個案及應用。
SEEM3650/ ESTR3516 Fundamentals in Decision and Data Analytics (決策與數據分析)
This course introduces the basic concepts of decision and data analytics from a statistical and probability view. Topics include linear regression, classification, sampling techniques, model selection, decision trees, principal component analysis, clustering, and their applications in decision making.
該科從統計和概率的角度介紹決策與數據分析,內容包括線性回歸,分類,抽樣,模型選擇,決策樹,主成分分析,聚類,以及其在決策分析中的應用。
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.
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。
SEEM4760/ ESTR4512 Stochastic Models for Decision Analytics (決策分析中的隨機模型)
This course introduces the concepts of stochastic models and their applications in decision analytics. It covers the topics of Markov chains, Markov decision processes, and various approximate dynamic programing techniques.
本科介紹隨機過程的基本理論以及其在決策分析中的應用,具體內容包括馬氏鏈,馬氏決策過程,以及多種近似動態規劃的方法。

FTEC4002 Behavioral Analytics (定量行為分析)
Behavioral 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。
SEEM2460/ ESTR2540 Introduction to Data Science (數據科學化基礎)
This course presents an introductory roadmap into the newly emerged and rapidly evolving field of data science, with the objective of introducing the problem-solving mindset in a data-intensive context. The course projects data science as a productive synthesis of its parent disciplines, including mathematics, statistics, computing, data mining, system science and data visualization, etc. Such a productive synthesis is applicable across many fields to bring about scientific discovery through data-intensive, analytical methods. This course aims to help navigate students in taking more advanced courses in its parent disciplines to build up their expertise in data science. We cover topics including: History and impact of Data Science. Collecting Data: sources, types and categorization of data. Visualising Data: summary statistics, data display, data dictionaries, schema and graphical visualization. Analysing Data: pattern recognition, correlations and relationships, hypotheses testing, statistical significance. Investigating Data: data mining, machine learning, inference, meta-data, modeling, eliciting meaning and validation. Applicational contexts: Examples of useful applications from case studies.
這科提供基礎藍圖幫助學習數據科學化,這是嶄新及急速發展的領域,目的是學習利用科學化的方法及分析大量數據來輔助解決實用問題,訓練學生具備相關的思維。 數據科學化牽涉各學科包括數學、統計、電子計算、數據挖掘、系統科學及數據視覺化。 它可應用於各領域,透過處理及分析數據來支持科學探索與發現。這科也可增加學生對相關學科的認識,幫助他們日後修讀更深入的科目,擁有數據科學化的專業技術。 科目範圍包括: 數據科學化的歷史及影響,數據採集: 來源、種類、範疇,數據視覺化: 數據顯示、數據字典,數據架構與圖像化,數據分析:模式識別、相關性、關聯性,假設檢驗、統計顯著性測試,數據研究:數據挖掘、機器學習、推理,元數據設計,數據模型,含義抽取及驗證,實用個案及應用。
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.
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。

SEEM3430 Information Systems Analysis and Design 資訊系統分析及設計
Information system development life cycle; user requirement analysis; feasibility study; cost/benefit analysis; systems analysis tools such as data flow diagrams and process specification tools. Real time systems analysis. Transformation from analysis to design. Structured chart. System design quality heuristics such as coupling and cohesion. System design packaging and design optimization: CASE (Computer-Aided Software Engineering) Tools.
資訊系統發展週期;用戶需求分析;可行性分析;成本 / 效益分析;系統分析工具如數據流程圖及過程說明工具。實時系統分析。由分析到設計之變換。結構圖表。評估系統設計質素之啟發方法:連接及聚合。系統設計之組裝及優化:CASE(計算機輔助軟件工程)工具。
SEEM3490 Information Systems Management (資訊系統管理)
In-depth discussion of the challenges, techniques and technologies associated with the management of IT in a competitive environment. The linkage of IT to business strategy and business process re-engineering. Type of information systems: MIS, DSS, TPS. Development process. Information system planning. Systems project management and control. IT acquisition, budgeting and deployment. Performance evaluation and auditing. Operations management. Privacy and security.
深入討論在現今激烈競爭下的資訊管理的挑戰、方法和技術。聯繫資訊管理和商業競爭策略以及再工程。資訊系統:DSS , MIS , TPS 。資訊系統的計劃,研究過程及管理。資訊系統的預算及分佈。效績評估和審核。運作管理。私隱權利和保安
SEEM3460/ ESTR3504 Computer Processing Systems Concepts (電腦處理系統概念)
Principles of operating system functions. Introduction to linkers, loaders, memory management and process management. Performance analysis of scheduling algorithm. Applications based on systems such as UNIX, Cloud computing concepts and their evaluation and selection based on application needs.
操作系統原理。匯編程序、連接程序、裝入程序、記憶管理及進程管理之介紹。UNIX 之應用。雲計算的概念及基於應用需要之評價與選擇。
SEEM4570 System Design and Implementation (系統設計及執行)
System implementation methodology construction, testing and maintenance. Software re-engineering and reverse engineering; software reliability and programme quality assurance; software reusability Software metrics. Performance engineering. Configuration management. Object-oriented system design. Use of computer-aided tools.
系統的執行方法、構成、測試及維護。軟件的重覆工程及反向工程;軟件的可靠性及程序品質的保證;軟件的再用性。軟件的量度制。系統功能的工程方法。結構管理。目標面向系統設計。計算機輔助工具使用。
SEEM4540 Open Systems for E-Commerce (電子商務的開放系統)
Overview the technologies and mechanisms of open systems. Advanced Internet applications including electronic commerce using open system and Web technologies. Multimedia applications over open systems. Applications on wireless and mobile network.
開放系統技術及機制的概述。互聯網的高層次應用:包括電子商務的開放系統及 Web 技術。開放系統上的多媒體應用。無線及移動網絡的應用。
SEEM4630 E-Commerce Data Mining (電子商務數據採集和分析)
This course introduces data mining techniques suitable for E-Commerce applications. It covers the following topics: prediction, association rule mining, rule induction, trend and deviation analysis, pattern visualization and data mining packages. Emphasis will be placed on employing these techniques to marketing, risk management, business negotiation and commercial applications.
本科介紹應用在電子商務的數據採集技術和分析。範圍包括推測法、關係常規搜集、常規推斷、趨勢及偏離分析、規律可視化及數據採集工具。本科集中討論應用上述技術在市場學、風險管理、商業談判及各商業上的問題。
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。
SEEM3510/ AIST3510 Human-computer Interaction (人機互動)
This course provides an introduction to the fast evolving field of human computer interaction (HCI). HCI is a multidisciplinary subject concerning the design, implemen-tation and evaluation of interactive computing systems for human use, and the study of major phenomena surrounding them. We will provide a broad overview of the field, including the theory and principles underlying good designs, with an emphasis on the interface design process, development and evaluation. We will also sample some state-of-the-art technologies in HCI, such as speech recognition, haptics, virtual reality, software agents and computer supported cooperative work.
人機互動設計的基礎,包括人類處理信息的模型及其理論、智能介面的設計方法、步驟及評估之方法。人機互動的要素:佈局、顯示、規約、對話、程序及誤差的處理。應用於人機互動的新科技:語音識別、觸感合成、虛擬真實、軟件代理、群體軟件等。
SEEM3680/ ESTR3512 Technology, Consulting and Analytics in Practice (實用科技諮詢及分析)
This course presents students with a broad overview of the latest technologies, e.g. cloud computing, social media, mobile applications, etc. that are impacting the business world everyday. Students are presented with case studies to illustrate how advanced technologies are used in solutions to real-world problems. Students will be presented with opportunities to adopt design thinking techniques to come up with innovative ideas for problem-solving, and optionally create pilot implementations of their design. The SEEM department will invite participation by industry leaders and practitioners to share their insights in this course.
這科目的是向學生介紹業界最新資訊科學技術,如雲端運算、社交媒體技術、移動計算等,並教授如何將科技應用在商業社會中,解決日常生活的問題。向學生介紹案例研究,以說明如何在解決現實問題的過程中使用先進技術。 學生將有機會採用設計思維技巧,提出解決問題的創新思路,並可選擇創建他們設計的試驗性實施。本學系亦會邀請業界領導和專家作經驗分享。
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。
FTEC4007 Introduction to Blockchain and Distributed Ledger Technology (區塊鏈及分布式分類帳技術介紹)
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.
本科介紹了加密貨幣、區塊鏈、分布式分類帳技術及其應用。學生會學習這些系統如何工作,以及如何開發軟件應用程序和比特幣網絡及其他加密貨幣的交互。
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.
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。
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 。
SEEM4720/ ESTR4506 Computational Finance (計算金融學)
In depth examination of numerical methods and their implementation for finance and risk management problems: Linear and Nonlinear Equation solutions, Unconstrained and constrained optimization, Monte Carlo Simulation, Finite difference for PDEs. Other related financial applications.
數值方法及其在金融和風險管理的應用:線性及非線性方程式的求解、局限及不局限下的優化,蒙地卡羅模擬法,偏微積分方程中的有限差分。其他相關的金融應用。
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.
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。
FTEC4002 Behavioral Analytics (定量行為分析)
Behavioral 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。
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。
MKTG2010 Marketing Management (市場管理)
This course is devoted to the study of the management of marketing functions, the analysis of external forces affecting marketing decision making, the implementation and control of marketing activities, and an examination of the global impact of marketing. Course objectives include the development of students’ understanding of the fundamental concepts underlying the selection and assessment of markets and the development and delivery of products, an investigation of the role and contribution of marketing to the conduct of successful business operation and to society, and to develop student abilities in identifying marketing opportunities and viable marketing strategies.
本科旨在研究市場管理之功能,分析環球和宏觀市場因素,在推動及控制市場策略時的互維關係。其目的在培育學生明白及掌握基本市場學理論、發展和營銷商品概念,探討如何因應市場不同的環境,作出評估及選擇適當的市場策略,為企業和社會創造雙嬴的結果,並發展學生的思維及分析才能,發掘市場機會及制訂可行的市場方案。
SEEM3620/ ESTR3514 Introduction to Logistics and Supply Chain Management (物流與供應鏈管理入門)
Logistics and Supply Chain Management involves various flows (e.g., materials flow and information flow) among all of the entities that contribute value to a product, from the source of raw materials to end customers. This course will focus on the basic concepts, models and techniques for effective strategic management of an integrated and coordinated supply chain. The emphasis is on recognizing key tradeoffs, analyzing system characteristics, and understanding effectiveness of tactics such as risk pooling, inventory policies, collaboration, and information sharing.
物流與供應鏈管理涉及如何管理材料流通,信息流通等各種各樣的在鏈條裡的流通。這些流通在物流與供應鏈裡廣泛存在,從原材料供應一直到終端顧客的各個相關方之間都極大地影響著整個系統之表現。本科著眼於為能進行有效管理物流與供應鏈而必須掌握的基本概念,模型,以及技術。主題包括發現關鍵權衡,分析系統特性,理解各種策略(例如風險共擔,庫存控制,合作,以及信息共享等)的有效性。
SEEM3500 Quality Control and Management (品質控制與管理)
Quality planning, control and improvement. Sampling theory. Statistical quality control theory applied to production operations. Specification and control charts for monitoring production systems. Quality engineering – the Taguchi Method. Quality control issues of manufacturing and service industry. Case studies of quality control problems in industry. Use of computer aids. Introduction to ISO 9000.
品質管理、控制與改進。採樣理論。生產運行中的統計品質控制理論。生產系統之監控規範和控制圖表。品質工程 - Taguchi 方法。製造和服務行業中的品質控制問題。工業品質控制問題之有關個案分析。計算機輔助工具之使用。ISO 9000導論。
SEEM4750/ ESTR4510 Advances in Logistics and Supply Chain Management (高級物流與供應鏈管理)
This course covers the advanced topics in logistics and supply chain management. In particular, it uses comprehensive models to describe, and hence explore the optimal strategies in, various important logistics and supply chain management problems. The topics include customer service, channels of distribution, transportation, vehicle routing and scheduling, freight consolidation, facility location and network planning, storage. This course also introduces important practice in logistics and supply chain management, such as material handling systems, information systems for order processing and inventory tracking, purchasing and supply scheduling, business process re-engineering, third-party logistics, and global logistics.
本科涵蓋了一系列物流與供應鏈管理的進階課題。具體而言,我們利用比較嚴謹的模型來描述一系列物流與供應鏈管理中的重要問題,並發掘其最優控制策略。主題包括顧客服務,分銷渠道,交通,車輛路徑規劃,並貨,設施選址及網絡規劃,存儲。本科同時也會介紹在物流與供應鏈業界中的重要實踐,例如原料處理系統,信息系統,採購及供應規劃,第三方物流,全球物流等等。
SEEM3630/ ESTR3510 Service Management (服務營運的管理)
Overview of the operations functions of service organizations. Examination of methods for designing and operating service delivery systems in the health care, financial, hospitality, telecommunication, and logistics industry. Discussion on service strategy, services for individual and corporate customers, service technologies, process and facility design, management of waiting lines, demand forecasting, demand and supply management, service quality, staffing and scheduling.
服務機構營運及操作的概要。檢視各種在保健、金融、旅遊、電訊及物流行業所使用的服務提供系統的設計和運作方法。探討下列課題─服務策略、個人及企業的服務、服務科技、程序及設施的設計、等候行列的管理、需求的預測、需求及供應的管理、服務的素質、人員配備及調度。
SEEM4670 Service Systems (服務系統)
Overview of the evolution of information systems and technologies used in selected service industries, such as health care, finance, insurance, hospitality, telecommunication, retail, etc. Examination of the unique features of a service system as a product or service. Qualitative and Quantitative methods for analyzing, designing, and operating service systems. User influence. Systems Development.
簡介運用於醫護、金融、保險、旅遊、電訊及零售各行業的服務系統。檢測服務系統作為產品或服務的特徵。分析、設計、營運系統的定性及定量方法。系統使用者的影響。系統開發的考慮。

As an optional choice, the program offers two streams of specialization. The stream of Business Information System focuses on the business information system aspect of data science and on applications in E-commence and technological innovation. The stream of Decision Analytics focuses on the decisions analytics aspect of data science and on applications in financial engineering, logistic and supply chain management, and service engineering and management.

STUDY SCHEMES

STUDY SCHEMES

Programme Title:           Systems Engineering and Engineering Management (SEEM)
Study Scheme Applicable to students admitted in 2023-24

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.Foundation Courses (all courses in group (a), one course from group (b), and one course from group (c) are required):

(a) ENGG2440/ESTR2004, ENGG2760/ESTR2018, ENGG2780/ESTR2020, MATH1510, SEEM2440/ESTR2500

(b) Programming Courses:
CSCI1120/ESTR1100, CSCI1130/ESTR1102

(c) Other Courses:
ENGG1310/ESTR1003, ENGG2720/ESTR2014, ENGG2740/ESTR2016, PHYS1003, PHYS1110, SEEM2460/ESTR2540
18
3.Required Courses:
(a) CSCI2040, CSCI2100/ESTR2102, SEEM2420, SEEM2602, SEEM3410, SEEM3440/ESTR3500, SEEM3450/ESTR3502, SEEM3550/ESTR3506, SEEM3650/ESTR3516

24
(b) Research Component Courses:
SEEM4998, SEEM4999
6
4Elective Courses:
AIST3510/SEEM3510, CSCI4140, ENGG1820, FTEC4001, FTEC4002, FTEC4005, FTEC4007, IERG4210, MKTG2010, SEEM2520, SEEM3430, SEEM3460/ESTR3504, SEEM3490, SEEM3500, SEEM3580, SEEM3590/ESTR3509, SEEM3620/ESTR3514, SEEM3630/ESTR3510, SEEM3680/ESTR3512, SEEM4540, SEEM4570, SEEM4630, SEEM4670, SEEM4720/ESTR4506, SEEM4730/ESTR4508, SEEM4750/ESTR4510, SEEM4760/ESTR4512
~
18
Total: 75

Programme Requirement

PROGRAMME REQUIREMENT

For reference only. Students should refer to Student Handbook in case of any inconsistency or ambiguity.

PROGRAMME DETAILS

Programme Details

internship

INTERNSHIPS

In the past, our students interned in a variety of institutions.

  • Commercial banks: e.g., HSBC Insurance (Asia) Limited, Hang Seng Bank Limited and The Hong Kong and Shanghai Banking Corporation Limited
  • Technology companies: e.g., Robert Bosch Co. Ltd. and FonFair Technology Lmited
  • Logistic: e.g., Kelly Services Hong Kong Limited
  • Insurance: e.g., Generali Life (Hong Kong) Limited and Swiss Reinsurance Co. Ltd
  • Consulting: e.g., Deloitte China
  • Regulation: e.g., Hong Kong Monetary Authority

All students are welcome to join Placement and Internship Programme (PIP). PIP offers a direct communication channel between our students and their potential employers. PIP offers opportunities of internships, career talks, seminars, summer jobs and placement which are collectively managed under the Student Placement and Internship Programme (PIP).

OVERSEA EXCHANGE

OVERSEAS EXCHANGE

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

  • Europe and Africa: e.g., Karlsruhe Institute of Technology, University College London, University of Bergen, The University of Liverpool, Technical University of Denmark, TELECOM SudParis, Katholieke Universiteit Leuven, University of Southampton, University of Economics, Prague
  • Asia: e.g., Shanghai Jiao Tong University, Soka University, University of Seoul, Seoul National University, International Christian University
  • Americas: e.g., University of Pennsylvania, Tecnologico de Monterrey, Rensselaer Polytechnic Institute, Dartmouth College, St. Edward’s University, University of Toronto

Academic Honesty

ACADEMIC HONESTY

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

alumni

ALUMNI


URL : http://alumni.se.cuhk.edu.hk