Postgraduate Courses
- CSIT 5100Engineering Reliable Object-Oriented Software Systems[3-0-0:3]Previous Course Code(s)CSIT 510DescriptionDiscussion of the latest enabling technologies used for the engineering of reliable software applications. These technologies include the modeling, design, testing and analysis of software applications.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply software engineering principles to develop and manage software systems.
- 2.Apply industrial practice and software tools to develop and manage software systems.
- CSIT 5110Multimedia Development[3-0-0:3]Previous Course Code(s)CSIT 511DescriptionMultimedia fundamentals and design issues. Audio fundamentals and audio processing. Image fundamentals and image processing. Video fundamentals and video processing. Internet multimedia. Integrated multimedia.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Explain different types of signals and how they can be controlled.
- 2.Create programs for the generation of audio and music.
- 3.Explain different colour models and how they may be applied.
- 4.Explain various algorithms for the processing of images.
- 5.Develop a multimedia project.
- CSIT 5130Building Applications for Computational Finance[3-0-0:3]Previous Course Code(s)CSIT 513, CSIT 600LBackgroundProgramming experienceDescriptionFinancial arithmetic and financial instruments overview. Introduces tools and technologies for building applications in computational finance. Familiarity with Excel functionalities and VBA programming skills. Advanced Excel C++ add-in development. Object oriented modeling and design.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply the time value of money and price fixed income instruments.
- 2.Translate financial models into spreadsheets applications.
- 3.Use VBA to build user defined functions.
- 4.Develop financial functions using Excel C++ add-in.
- CSIT 5210Data Mining and Knowledge Discovery[3-0-0:3]Previous Course Code(s)CSIT 521Co-list withMSBD 5002Exclusion(s)COMP 5331, MSBD 5002DescriptionData mining has recently emerged as a major field of research and applications. Aimed at extracting useful and interesting knowledge from large data repositories such as databases and the Web, data mining integrates techniques from the fields of database, statistics and AI.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply the clustering techniques to find clusters within the data.
- 2.Use the classification techniques to conduct classification and predication.
- 3.Use the knowledge of frequent pattern mining to discover patterns from the data.
- 4.Conduct mining over social media and text data and detect outliers from the data.
- CSIT 5220Reasoning and Decision under Uncertainty[3-0-0:3]Previous Course Code(s)CSIT 600NDescriptionIn management decisions are often made in the face of uncertainty. This course covers computational tools for supporting reasoning and decision making under uncertainty. Topics include probabilistic inference, Bayesian networks, decision analysis, decision graphs, model building, model learning, solution algorithms, real-world examples and software tools.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Examine complex decision problems that involve multiple uncertain factors and formulate them as computational problems.
- 2.Solve complex decision problems using Bayesian networks and decision graphs.
- 3.Define the methods for learning the structures and parameters of Bayesian networks.
- 4.Recognize the software tools for reasoning and decision under uncertainty.
- CSIT 5300Advanced Database Systems[3-0-0:3]Previous Course Code(s)CSIT 530DescriptionThis advanced database course addresses a number of selected data management issues and introduces emerging database related techniques.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Describe important concepts in database management systems, including conceptual modeling and data models, logical and physical database design, and query languages.
- 2.Describe a number of data management issues, including query processing and optimization, transaction management, and concurrency control protocols.
- 3.Apply database theories to practical database design and application development.
- CSIT 5400Computer Graphics[3-0-0:3]Previous Course Code(s)CSIT 540Exclusion(s)COMP 5411DescriptionIntroduction to image synthesis and digital modeling. Topics include color theory, image processing, affine and projective geometry, hidden-surface determination, photorealistic image synthesis, advanced curve and surface design, dynamics, realistic character animation.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Explain algorithms for processing the pixel representation of an image.
- 2.Explain the fundamentals of the graphics rendering pipeline.
- 3.Use appropriate mathematics at various stages in the graphics pipeline.
- 4.Explain and apply techniques, such as light representation, texture mapping and shadow generation, in the generation of realistic graphics output.
- 5.Discuss the basic techniques of global illumination.
- 6.Develop basic programs on the GPU to generate graphics output.
- CSIT 5410Recognition Systems[3-0-0:3]Previous Course Code(s)CSIT 600MDescriptionIt is getting easier and more and more common to install or use recognition systems in our daily lives and working environments, such as fingerprint recognition systems, face and iris recognition systems, car plate and vehicle recognition systems, industrial automation inspection systems, medical diagnosis and surgical planning systems, image search systems. This course aims to provide students with a sound background in the area of recognition systems. Tentative topics include various examples of recognition systems, and related techniques in image analysis, computer vision, and pattern recognition.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Identify concepts and techniques to recognize image features and patterns.
- 2.Identify concepts and techniques to recognize different objects, e.g. iris, face, fingerprint, license plate and vehicle.
- CSIT 5500Advanced Algorithms[3-0-0:3]Previous Course Code(s)CSIT 6000EDescriptionThis course covers some advanced algorithms. Topics include sorting and data structures, divide and conquer, string processing, dynamic programming, graph algorithms, shortest path, maximum flow, stable marriage, and streaming.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Analyze the time and space efficiency of an algorithm as a function of the size of a problem instance.
- 2.Apply advanced algorithmic design and analysis techniques to solve problems.
- 3.Identify various data structures and apply them in designing algorithms.
- 4.Explain the correctness of algorithms.
- 5.Describe and apply some advanced algorithms for combinatorial optimization and graph problems.
- CSIT 5510Mobile Application Development[3-0-0:3]Previous Course Code(s)CSIT 6000BDescriptionPrinciples of mobile application development. Mobile software development environments and software architectures. Event-driven Programming. The Model-View-Controller framework. Features of typical mobile platforms: User-interface and user-experience design, Multimedia, 2D and 3D graphics and data storage support, networking, location and mapping services. Mobile client-server communication. Mobile back-end support. Hybrid mobile applications. Students need to design and implement a full-fledged mobile application.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Design and implement a full-fledged mobile application based on the latest mobile software development techniques.
- 2.Integrate theoretical principles with up-to-date techniques in mobile application development.
- 3.Communicate effectively through report writing, literature search, project design and oral presentations.
- 4.Apply the latest mobile software development tools and techniques, especially state-of-the-art techniques that are used in industrial practice.
- 5.Identify and describe the impact of key factors related to the design, management and performance of mobile applications.
- CSIT 5600Internet Infrastructure: Switches and Routers[3-0-0:3]Previous Course Code(s)CSIT 560DescriptionThe design and analysis of electronic/optical switches/routers needed to support the development and delivery of advanced network services over the Internet. Switches and routers are the KEY building blocks of the Internet.
- CSIT 5610Computer Networks: An Internet Perspective[3-0-0:3]Previous Course Code(s)CSIT 561DescriptionThis course discusses in-depth the architectures, protocols, and other key issues in the design of the global Internet. Topics include: common Internet applications, layered network architecture, switching techniques, local area networks, routing, transport, and multimedia networking.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Define and describe the basic working principles of computer networks, their architecture and protocols.
- 2.Describe the principles of networked applications, including client-server based applications (e.g. HTTP, FTP, SMTP and DNS) and peer-to-peer based applications (e.g. BitTorrent, Skype, etc.).
- 3.Discuss transport layer protocols, such as TCP and UDP, and recognize their functions and the services they provide.
- 4.Explain congestion in computer networks, its manifestations and its causes, and discuss congestion control mechanisms available in the Internet to tackle it.
- 5.Illustrate the principles of network layer services and discuss routing algorithms and their applications in the Internet.
- 6.Describe the services of the link layer and identify basic link layer protocols and medium access mechanisms.
- CSIT 5710Cryptography and Security[3-0-0:3]Previous Course Code(s)CSIT 571Exclusion(s)COMP 5631DescriptionThe design and analysis of ciphers, public-key cryptography, digital signature, user and data authentication, nonrepudiation, data integrity, public-key infrastructure, secret sharing, key management, cryptographic protocols, systems security, network security, and Web security.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Identify and formulate security problems in information technology.
- 2.Apply and integrate security principles for solving security problems in information technology.
- 3.Communicate effectively through assignment writing and project designing.
- CSIT 5720Digital Forensic and Legal Issues[3-0-0:3]Previous Course Code(s)CSIT 572, CSIT 600IDescriptionThis course will cover the current computer crime legislations, cases involving Internet crimes, personal data privacy, e-business transactions and intellectual property right (IPR) issues, and explain how computer forensics and digital evidence analysis can enhance corporate information security strategies, IT audit and incident management. Case studies in financial computing (algo-trading/high frequency trading) and digital forensics, and hands-on session using digital forensics tools will be introduced.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Apply the current IT laws in Hong Kong and the United Nation model laws in digital asset protection, intellectual property right, and personal data privacy issues in corporate IT and security policy formulation and practices.
- 2.Examine and evaluate the corporate IT and HR policies to enhance data protection and cyber security.
- 3.Analyze both the legal and technical aspects of e-Business litigation, e-Discovery and IT security breaches at corporate level.
- 4.Communicate effectively with the corporate executives, legal counsels, auditors and law enforcement agencies when dealing with e-Business disputes, IT crime and digital evidence.
- 5.Identify the key features and/or control measures in IT architectural design and implementation for the preservation of data (digital evidence) integrity and authenticity.
- 6.Enhance their perspectives and careers from technical level to corporate managerial level when researching, developing and launching innovative IT products/services.
- CSIT 5800Introduction to Big Data[3-0-0:3]Previous Course Code(s)CSIT 6000DDescriptionThis course aims at providing students with the fundamental concepts and overview of Big Data, and engaging in open discussion about the challenges and opportunities that it brought about. Topics to be covered include: Properties of Big Data, Big Data Integration, Big Data Mining, and Technologies and Tools on Big Data Analytics.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Explain what Big Data is and the impact of Big Data to the society.
- 2.Identify the characteristics and the challenges of Big Data.
- 3.Describe the steps involved in the process of Big Data analysis, including data collection, data preprocessing, data integration, and data mining.
- 4.Apply working knowledge on how to structure the analysis with the steps of Big Data analysis process.
- 5.Apply Big Data analytics technologies to discover the information hidden in vast amount of data.
- CSIT 6000Topics in Information Technology[1-3 credit(s)]Previous Course Code(s)CSIT 600DescriptionState-of-the-art topics in Information Technology reflecting recent developments in techniques and tools.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Identify the major issues and technical problems in a specific topic in information technology.
- 2.Recognize key technical solutions to the problems in the topic.
- 3.Solve specific problems in the topic.
- CSIT 6910Independent Project[1-3 credit(s)]Previous Course Code(s)CSIT 691DescriptionAn independent project carried out under the supervision of a faculty member. This course may be repeated for credit.Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.Identify the state of the art of the topic.
- 2.Gain experience in doing research or self-learning.
- 3.Solve real-world problems independently.