Undergraduate Courses 2017-18

A compulsory one-year course for students of the Department of Computer Science and Engineering. This course is designed to provide academic advising to students and to develop their communication skills in interacting with technical and non-technical audiences.

Interesting and useful things you can do on the computer, but take time to learn. Introduction to multimedia and internet computing tools. Internet, e-mail, WWW, webpage design, computer animation, spreadsheet charts/figures, presentations with graphics and animations, etc. Business, security, accessibility, and relevant IP right issues in the use of computers.

Introduction to computers and programming. Computer hardware and software. Problem solving. Program design. Procedural abstraction. Debugging and testing. Simple and structured data types. Recursive programming. Introduction to searching and sorting.

This is a one semester course equipping students with the fundamental concepts of programming using Excel VBA. Students will first learn how to use Excel to analyze and present data, and will then learn how to use VBA code to build powerful programs.

Programming techniques and introduction to object-oriented programming. Classes and objects. Data encapsulation and information hiding. Abstract data types. Pointers and linked data structures. Recursive data structures. Searching and sorting.

Structured programming and introduction to object-oriented programming. Problem solving. Program design. Procedural abstraction. Debugging and testing. Classes, objects, and dynamic objects. Abstract data types. Linked data structures. Searching, sorting, and recursive programming.

Extensive study of the C programming language: program structure, functions, control flow, pointers, arrays, structures, file input and output; use of programming tools in the UNIX environment; relevant programming techniques. Prerequisite: COMP102

Unix utilities and file structure; links and symbolic links; data processing and process control in the Unix shell; Shell programming; regular expressions; script programming in the Unix environment. Laboratory exercises are designed to give hands-on practice with software tools and to increase programmer productivity.

To learn the fundamental concepts and techniques behind object-oriented programming. They include: abstract data types; creation, initialization, and destruction of objects; class hierarchies; polymorphism, inheritance and dynamic binding; generic programming using templates. To learn the object-oriented view of data structures: linked lists, queues, stacks, trees, and algorithms such as searching, sorting, and hashing algorithms.

To learn data structures in an object-oriented programming language. Abstract data types such as: sequences, maps/dictionaries, stacks, priority queues. Class hierarchies and inheritance; polymorphism; early and late binding; static and dynamic object-oriented programming; generic programming, templates, and algorithm abstraction. Data structures such as: linked lists, trees, heaps, tries, graphs, hash tables. Sorting and search algorithms: asymptotic notations, complexity analysis, and lower bound. Enrollment in the course requires approval of the course instructor.

Basic concepts in discrete mathematics needed for the study of computer science: enumeration techniques, basic number theory, logic and proofs, recursion and recurrences, probability theory and graph theory. The approach of this course is specifically computer science application oriented.

Inner workings of modern digital computer systems and tradeoffs at the hardware-software interface. Topics include: instructions set design, memory systems, input-output systems, interrupts and exceptions, pipelining, performance and cost analysis, assembly language programming, and a survey of advanced architectures.

Studies under the directed guidance of a faculty member on a computer science topic at 100-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study.

Continuation of COMP 001. A compulsory, one year course for students of the Department of Computer Science and Engineering.

Introduction to Java programming. Fundamentals include language syntax, object-oriented programming, inheritance, polymorphism, exception handling, multithreading. Standard libraries for input/output, graphics programming, built-in data structures. Programming for events, web, networking, generics.

Foundations underlying design of intelligent systems. Relations between logical, statistical, cognitive, biological paradigms; basic techniques for heuristic search, theorem proving, knowledge representation, adaptation; applications in vision, language, planning, expert systems.

Principles of database systems; conceptual modeling and data models; logical and physical database design; query languages and query processing; database services including concurrency, crash recovery, security and integrity. Hands-on DBMS experience.

Comparative studies of programming languages, programming language concepts and constructs. Non-imperative programming paradigms: object-oriented, functional, logic, concurrent programming. Basic concepts of program translation and interpretation. Storage allocation and run-time organization.

Principles, purpose and structure of operating systems; processes, threads, and multi-threaded programming; CPU scheduling; synchronization, mutual exclusion; memory management and virtual memory; device management; file systems, security and protection.

Techniques for designing algorithms, proving their correctness, and analyzing their running times. Topics covered include: sorting, selection, heaps, balanced search trees, divide-and-conquer, greedy algorithms, dynamic programming, and graph algorithms.

Time and space complexity analysis of algorithms. Design paradigms: divide-and-conquer, greedy algorithms, dynamic programming. Graph algorithms: searching and backtracking, connectivity, biconnectivity, minimum spanning tree, shortest path. Fast Fourier Transform. Network flow. RSA and public key encryption. Randomized and amortized analysis. NP-completeness. Enrollment in the course requires approval of the course instructor.

Studies under the directed guidance of a faculty member on a computer science topic at 200-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study.

Intensive programming laboratory to equip students with creative problem solving and competitive programming skills. International programming competition-type problems will be used to motivate the study of algorithms, programming, and other topics in computer science. Enrollment in the course requires approval of the course instructor.

Continuation of COMP 002. A compulsory, one year course for students of the Department of Computer Science and Engineering.

Selected topics of current interest to the Department not covered by existing courses. Offerings are announced each semester.

Convex hull, plane-sweep, triangulation, linear programming, range searching, point location, Voronoi diagram, arrangements, Delaunay triangulation, and geometric data structures. Prerequisite: COMP271

Computer game development touches on many facets of computer science, including computer graphics, artificial intelligence, algorithms, networking, and human-computer interaction. This course mainly focuses on the 3D graphics programming aspect of game development, while briefly covering some of these other components. Students will get hands-on experience on how to design and implement real-world computer games. By taking this course, students will also perfect their skills in programming, teamwork, management, and communication. Students are expected to have good programming background in C++ which is needed to complete a group project in computer game in the final part of the course. Prerequisite: COMP341

At its best, computer science is an exciting blend of programming, mathematics, and problem solving. This course will introduce an interesting variety of subjects in programming, algorithms, and discrete mathematics though puzzles and problems which have appeared in the International ACM Programming Contest and similar venues. Prerequisite: COMP171

An introduction and exploration of Computer Science. Topics include programming essentials, data structures, logic, problem solving, computer graphics, GUI design, and Internet communication. Projects will be developed using the Python language. No previous programming experience is required. This is intended for preparatory year students only. Enrollment is subject to instructor's approval.

This course provides an in-depth introduction to Bioinformatics - an interdisciplinary subject - from the perspective of Computer Science. The course includes a primer of molecular biology, a review of algorithms & complexity, and a series of lectures & discussions on selected problems in Bioinformatics. Exclusion: BISC358 Prerequisite: COMP271 or COMP271H

Human language technology for processing text and spoken language. Fundamental machine learning, syntactic parsing, semantic interpretation, and context models, algorithms, and techniques. Applications include machine translation, web technologies, text mining, knowledge management, cognitive modeling, intelligent dialog systems, and computational linguistics.

Object-Oriented Concepts: abstraction, encapsulation, modularity, hierarchy, typing, concurrency, and persistence; object-Oriented Methods: graphical notations for object-oriented analysis and design, object-oriented process, the pragmatics of object-oriented development; and Applications.

Introduction to expert systems. Problem specification, architecture, knowledge representation, inference techniques, CLIPS programming. Prerequisites: COMP221 and COMP251

Introduction to Java programming. Fundamentals include language syntax, object-oriented programming, inheritance, polymorphism, exception handling, multithreading. Standard libraries for input/output, graphics programming, built-in data structures. Application programming interface (JFC/Swing). Prerequisite: COMP251 Exclusions: COMP300T, ISMT332

Technologies and standards for World Wide Web (WWW), user interfaces and Browsers, authoring tools, Internet protocols, Internet servers, database connectivity, Robots, Search engines, server-side programming, client-side programming, security and privacy, recent advances.

Basic elements of starting a new business in information technology; exploiting an "unfair" advantage; preparing a business plan; arranging financial support; accounting and legal requirements; exit strategy. Case studies of successful and failed ventures in Hong Kong and elsewhere. Enrollment is subject to instructor's approval.

Methods and tools for planning, designing, implementing, validating, and maintaining large software systems. Project work to build a software system as a team, using appropriate software engineering tools and techniques.

Methods and tools for planning, designing, implementing, validating, and maintaining large software systems. A student-defined project allows students to build a software system as a team, using appropriate software engineering tools and techniques. Enrollment in the course requires approval of the course instructor.

Introduction to automata, formal languages, and computability. Set theory and countability. Finite automata and regular languages. Push-down automata and context-free languages. Turing machines. Church's thesis. Halting problem. Uncomputability.

Data modeling concepts; conceptual, logical and physical design; analyzing, evaluating and improving schemas; schema documentation and maintenance; functional analysis; design tools; schema mappings; database tuning; distributed database design.

Text retrieval models, vector space model, document ranking, performance evaluation; indexing, pattern matching, relevance feedback, clustering; web search engines, authority-based ranking; enterprise data management, content creation, meta data, taxonomy, ontology; semantic web, digital libraries and knowledge management applications.

This course will provide an introduction to concepts and techniques in the field of data mining. Materials include an introduction to data warehousing and OLAP, data preprocessing and the techniques used to explore the large quantities of data for the discovery of predictive models and knowledge. The course will include techniques such as nearest neighbor, decision tress, neural networks, Bayesian networks and Na? Bayes, rule-based methods, association analysis and clustering, as well as social networks and data mining applications in business and finance applications, and other emerging data mining subareas. Students learn the materials by attending lectures and implementing and applying different data analysis and mining techniques to large datasets throughout the semester.

Display technologies; scan conversion; clipping; affine transformations; homogeneous coordinates and projection; viewing transformations; hidden surface removal; reflectance and shading models; ray tracing; spline curves and surfaces; hierarchical modeling; texture mapping; color models.

Color theory; digital audio, image and video fundamentals, representation, and processing; digital multimedia applications and programming.

Introduction to image processing. Topics include image processing and analysis in spatial and frequency domains, image restoration and compression, image segmentation and registration, morphological image processing, representation and description, related application areas and some other closely related topics. Some sophisticated image processing and analysis tools and state-of-the-art methods may also be introduced subject to the availability of time.

Principles of software design and implementation for embedded systems; Timing, power, size and mobility constraints in embedded software design; basic hardware concepts; interrupts and interrupt handling; embedded operating system issues; real-time scheduling; real-time operating systems; embedded software development; integrated design environments; embedded networking; formal design methodologies, design examples.

Principles of computer network architectures and communication protocols; the OSI reference model; switching and multiplexing techniques; data link, network, transport and application layers; LAN and medium access protocols; network programming.

Multimedia requirements; bridges and their spanning tree protocol; advanced internet protocols (IPv6, Diffserv, IntServ, etc.); congestion control and QoS; multicast and broadcast algorithms; network performance and programming; introduction to network security.

Cryptosystems, symmetric-key and public-key cryptography, cryptanalysis, authentication, message digests, digital signatures, and random number generation. Access controls and firewalls. Applications such as certificate authorities, electronic commerce, smartcards, and digital cash.

Analysis, synthesis and evaluation of different computer architectures. Emphasis on computer design with respect to price/performance and its relation to architectural choices such as pipelining, memory hierarchy, input/output, instruction set design, vector processing, and multiprocessing.

Only for honors students of the BEng Computer Engineering program. Students must take the whole course series comprising COMP/ELEC 387, 388 and 389 in sequence. They are expected to conduct research/independent work under the supervision of a faculty member of the Department of Computer Science and Engineering and/or Department of Electronic and Computer Engineering, summarize their work in an individual thesis and make a presentation at the end of the sequence. Work on COMP/ELEC 387 normally commences in the summer following the second year. May be graded PP.

Only for honors students of the BEng Computer Engineering program. Continuation of COMP 387. May be graded PP.

Only for honors students of the BEng Computer Engineering program. Continuation of COMP 388.

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study.

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study.

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study.

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study. Prerequisite: CGA at grade A- or above

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study. Prerequisite: CGA at grade A- or above

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study. Prerequisite: CGA at grade A- or above

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study. Prerequisite: CGA at grade A- or above

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study. Prerequisite: CGA at grade A- or above

Studies under the directed guidance of a faculty member on a computer science topic at 300-level. A written report and/or an examination are required. Enrollment in the course requires approval of the course instructor. Courses may last for two semesters, depending on the topic and scope of study. Prerequisite: CGA at grade A- or above

[Also ELEC 394] Each Computer Engineering student is required to take COMP/ELEC 394, 395 and 396. The project is conducted under the supervision of a faculty member of the Department of Computer Science and Engineering and/or Department of Electronic and Computer Engineering. May be graded PP.

[Also ELEC 395] Continuation of COMP 394. May be graded PP.

[Also ELEC 396] Continuation of COMP 395.

Students must take the whole course series comprising COMP 397H and COMP 398H in sequence. They are expected to conduct research work under the supervision of a faculty member, summarize their work in an individual thesis and make a presentation at the end of the sequence. Enrollment in the course requires approval of the course instructor. May be graded PP.

Continuation of COMP 397H.

Fundamentals of machine learning. Concept learning. Evaluating hypotheses. Supervised learning, unsupervised learning and reinforcement learning. Bayesian learning. Ensemble Methods.

A project in an area of specialization in Computer Science under the guidance of a faculty member. Objectives are to integrate the classroom material from several courses, and to apply them to solve practical problems. May be graded PP.

CSE FYP

For students of the Department of Computer Science and Engineering only. A practical training course for a period of three weeks. Topics include Linux system administration, Linux network administration, managing and maintaining a Windows server environment, and safety.