本硕士课程旨在深化学生对人工智能和机器学习的知识与理解,为进入计算行业做好准备。课程将培养学生在人工智能领域的专业知识,确保他们掌握最新技术,并能应用这些技术解决问题和开发应用。学生还将探索新兴趋势,并掌握Prolog、Matlab或Python等语言的实用编程技能。
核心模块包括:MSc Computing (Specialist) Individual Project(个人项目)、Mathematics for Machine Learning(机器学习数学)。选修模块分为两组:Group 1包括Logic-Based Learning、Computational Optimisation、Deep Learning、Machine Learning for Imaging、Natural Language Processing、Probabilistic Inference、Reinforcement Learning、Formal Methods for Safe AI、Prolog、Introduction to Machine Learning、Computer Vision、Robot Learning、Computational Neurodynamics、Deep Graph-Based Learning、Human-Robot Interaction、Methods and Tools in the Theory of Computing、Statistical Information Theory、Software Engineering for Machine Learning Systems、Non-Euclidean Methods in Machine Learning、Machine Learning Systems and Hardware;Group 2包括Robotics、Advanced Computer Architecture、Graphics、Custom Computing、Distributed Algorithms、Network and Web Security、System Performance Engineering。