Students will be required to take all the FOUR required courses plus ONE of the elective courses as listed below, i.e. 15 credits in total for the stream requirements. All of the following courses are three credits each.
Artificial intelligence is the study of intelligent agents. Due to the continued success of applying artificial intelligence to different challenging problems requiring high-level intelligence, there is an explosive interest in this field for scientists, dreamers, entrepreneurs and educators. This course is designed for students to understand and appreciate the basic principles of artificial intelligence. It covers computational intelligent systems, which can support decision making, interact with humans, navigate vehicles and achieve many other interesting and useful tasks. These intelligent systems are extremely useful in business, science, the humanities and other fields.
Artificial intelligence is the study of intelligent agents. Due to the continued success of applying artificial intelligence to different challenging problems requiring high-level intelligence, there is an explosive interest in this field for scientists, dreamers, entrepreneurs and educators. This course is designed for students to understand and appreciate the basic principles of artificial intelligence. It covers computational intelligent systems, which can support decision making, interact with humans, navigate vehicles and achieve many other interesting and useful tasks. These intelligent systems are extremely useful in business, science, the humanities and other fields.
Adopting location intelligence by analysing location-based data using a geographical information system (GIS) in business is becoming a success strategy in the competitive global economy. This course introduces students to how location-based data and information can facilitate business professionals to extract, analyse, interpret and visualise business data in maps. The traditional means of business analytics usually present results in spreadsheets, bar graphs or simple charts. Maps allow business professionals to reveal the underlying proximity relationships and trends in their data. Linking to different data sets enables more useful analytics, leading to more informed decisions and better outcomes. Case studies of location-based services and application examples are elaborated.
The purpose of this course is to cover the parts of calculus that are most relevant to economics and business, with an emphasis on mathematical optimization questions – finding a choice of variables that maximizes a function (e.g., utility or expected return) or minimizes a function (e.g., cost and risk) in the presence of constraints (e.g., feasibility and limited resources). This course covers foundational topics from multivariable calculus and linear algebra, topics from introductory analysis (e.g., open/closed sets, compactness, maximum theorem and implicit function theorem) and problems in unconstrained and constrained optimization (e.g., Lagrange multipliers, Kuhn-Tucker conditions and applications of convexity). Topics in linear programming and calculus of variations may also be discussed.
(Senior Year Admission)
https://www.ln.edu.hk/admissions/ug/senior-year/senior-year-admission