南安普頓大學(xué)馬來西亞校區(qū)

Electrical and electronic engineering drives the fundamental technologies of today’s connected world. Every area of our lives, from energy supply and transmission, medicine and healthcare to industrial applications, global trade, transport, communications, entertainment and security, is dependent on electrical and electronic technology. As a result, electrical and electronic engineering is now one of the fastest growing job fields in the world and skilled electrical and electronic engineers are very much in demand.

Course Content

At Southampton, we will ensure that you have a thorough grounding in a wide range of technologies. Our project work will enable you to acquire valuable skills in teamwork, project planning, time-management and presentation, applying your learning to design and build problems, and working to a brief. All of these will stand you in good stead as you move into your career.

This degree develops the technical and project management skills needed to become a leader in the electrical and electronics industry. It covers topics ranging from the technologies of electrical power and control to analogue and digital electronics and computing. The first two years will cover the breadth of electrical and electronic engineering. In years three and four, you can tailor your studies according to your interests through the wide range of option modules available.

MEng Electrical and Electronic Engineering pathways

All students on this programme gain a fundamental understanding across electrical and electronic engineering principles, however the various pathways (some of which are shown below) allow you to specialise further in particular areas by choosing optional modules.

Artificial Intelligence

This pathway will focus on the design and implementation of state-of-the art artificial intelligence techniques and algorithms. Taking modules linked to artificial intelligence will allow you to study the application and implementation of these modern techniques for image processing and computer vision, machine learning, robotic systems, smart-grid, computational biology and finance.