DS Course List

STAT2003 Advanced Statistics


This course introduces the basic probability theory and theoretical statistics (probability distributions, estimation and hypothesis test criteria, etc.) so that the students can understand the foundations of general statistical practices and are also well prepared for the advanced subjects like regression analysis, multivariate analysis, and time series forecasting.

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GCVM1013 Applied Ethics in Science and Technology


This course begins with a brief introduction to ethical theories and principles focusing on some of the issues that are at once universal and timeless. Through discussion, debates, and studying particular cases (from personal stories, newspapers, magazines and films etc.), it is hoped that students will be able to reflect critically on real life issues and make their own decisions. Ethical issues in selected fields according to the students’ majors will be chosen and students will be encouraged to apply the theories they learn.

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STAT3033 Bayesian Statistics


This course will present the relevant theory, methodology and computational techniques of modern Bayesian inference and modelling. The main emphasis of the course will be on how to use the Bayesian thinking, modelling and computation to analyse data with complex structure.

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MATH1073 Calculus I

微积分 I

This course introduces the basic ideas and techniques in single variable calculus with mathematical rigour to prepare students for more advanced mathematical and statistical subjects.

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MATH1083 Calculus II

微积分 II

This course is a continuation of Calculus I. It provides a solid foundation in multivariable calculus to prepare students for more advanced mathematics and statistical subjects.

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STAT4043 Categorical Data Analysis


To equip students with statistical methods for analysing categorical data arisen from qualitative response variables which cannot be handled by methods dealing with quantitative response, such as regression and ANOVA. Some computing software, such as SAS, S-PLUS, R or MATLAB, will be used to implement the methods. The learning outcome will be the ability to formulate suitable statistical models for qualitative response variables and to analyse such data with computer software.

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GCCH1013 Chinese Thought through the Ages


(1) introduce important thought that have produced extremely important and significant impact on Chinese social development from past to present; (2) make a connection with contemporary social status by selecting a number of philosophical issues such as harmony, homogeneity/heterogeneity, conflict and unity, diversity and sustainability etc.; (3) analyse how ‘the past affects the present’, and how Chinese traditional thought has influenced the development and evolvement of contemporary Chinese society; and (4) help the students to have a better understanding of Chinese thought through different historical periods and to strengthen their sense of identity.

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COMP4113 Computer Vision and Pattern Recognition


This course covers basic concepts in computer vision and pattern recognition. Topics include image sensing and camera perception, 2D image analysis such as filters, edge detection and Hough transform, pattern classification, physics-based vision, stereo and motion, and solid model recognition. It concludes with current trends and challenges in computer vision and pattern recognition.

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COMP4023 Computer and Network Security


This course introduces the fundamental concepts and techniques in computer and network security. Topics include basic encryption techniques, cryptographic algorithms, authentication and digital signature, public key infrastructure, access control, security models, as well as their applications to, for example, IP security, Web security, and trusted operating systems. In addition, it discusses other system and programming related security issues, including non-malicious errors, computer viruses, and intrusion detection.

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DS4013 Data Mining (For DS students)


This course introduces latest development of knowledge discovery and data mining concepts and emphasizes on data mining techniques, including data pre-processing, classification, clustering, data association and data warehouse. It can motivate students to analyse big data with modern software.

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DS2013 Data Processing Workshop I

数据处理工作坊 I

This workshop aims to lead students to learn independent design, research, and coding on database development. It will help students understand the concept of applying database to solve problems. By building web applications in groups, students will learn how to cooperate with team members, how to document, design, develop, and test web applications, and practice cutting edge software development technologies.

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DS3003 Data Processing Workshop II

数据处理工作坊 II

This workshop aims to help students have some practices in working on big data processing. The course will also give a brief introduction of Hadoop platform and how to use Hadoop to do big data analytics. The students are expected to have a clear understanding of Hadoop and its application after this course.

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DS3013 Data Processing Workshop III

数据处理工作坊 III

This workshop aims at machine learning with big data. In particular, different machine learning techniques in big data scenario are investigated.

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COMP2003 Data Structures and Algorithms


This course develops students’ knowledge of data structures and their associated algorithms. It introduces the concepts and techniques of structuring and operating on Abstract Data Types in problem solving. Common sorting, searching and graph algorithms will be discussed, and their complexity studied.

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COMP4053 Database System Implementation


This course provides students with an in-depth knowledge of relational database management systems (DBMS). Topics include data storage, index structures, query evaluation, transaction processing, concurrency control, and crash recovery. In addition, advanced topics such as distributed databases and data warehouses will also be covered.

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