香港大学：
在当今科技发达的时代，人工智能在我们日常生活中的不可或缺是不可否认的。随着智能机器渗透到社会的方方面面，提高效率和增强人类能力的优势已经显现出来。人工智能的一个显著方面是机器学习，它使机器能够观察、分析甚至犯错误，类似于人脑，而无需明确编程。因此，人工智能在科学研究、交通和营销等多个领域都有应用。展望未来，人工智能专业人才的需求预计将继续增长。
作为亚洲的全球大学，我们渴望培养一代专业的人工智能人才来满足市场需求。人工智能理学硕士课程为学生提供人工智能的基本原理和知识，并培养他们应用人工智能以道德意识解决现实世界问题的实践技能和能力。该计划旨在让毕业生为人工智能相关领域的广泛职业机会做好准备。
专业：Master of Science in Artificial Intelligence 人工智能理学硕士
学费：港币330000*，用于2024-25学年。全日制学习的费用通常分三期支付，为期1.5年。Normative: 1.5 years
此外，学生还需支付学费（港币350元）和毕业费（港币350美元）。所有全日制学生将获收取每年100港元的学生活动费，以支持学生会的活动及校园内的学生活动。
录取要求：Programme Entrance Requirements
A Bachelor's degree or an equivalent qualification;
Applicants should possess knowledge of linear algebra, calculus, probability theory, introductory statistics and computer programming; and
Fulfil the University Entrance Requirements.
课程：
| Total Credit Requirements | 总要求 |
|---|---|
| 72 credits | 72学分 |
| Compulsory Courses (42 credits) | 必修课（42学分） |
| ARIN7001 Foundations of artificial intelligence | ARIN7001人工智能基础 |
| ARIN7011 Optimization in artificial intelligence | ARIN7011人工智能中的优化 |
| ARIN7013 Numerical methods in artificial intelligence | ARIN7013人工智能中的数值方法 |
| ARIN7101 Statistics in artificial intelligence | ARIN7101人工智能统计 |
| ARIN7102 Applied data mining and text analytics | ARIN7102应用数据挖掘和文本分析 |
| COMP7404 Computational intelligence and machine learning | COMP7404计算智能与机器学习 |
| DASC7606 Deep learning | DASC7066深度学习 |
| Disciplinary Electives (18 credits)* | 学科选修课（18学分）* |
| with at least 6 credits from each of the following lists | 以下每个列表中至少有6个学分 |
| List A: | 列表A： |
| ARIN7014 Topics in advanced numerical analysis | ARIN7014高级数值分析主题 |
| ARIN7015 Topics in artificial intelligence and machine learning | ARIN7015人工智能和机器学习主题 |
| MATH7224 Topics in advanced probability theory | MATH7224高级概率论主题 |
| MATH7502 Topics in applied discrete mathematics | MATH7502应用离散数学主题 |
| MATH7503 Topics in advanced optimization | MATH7503高级优化主题 |
| List B: | 清单B: |
| STAT6011 Computational statistics and Bayesian learning | STAT6011计算统计学与贝叶斯学习 |
| STAT7008 Programming for data science | STAT7008数据科学编程 |
| STAT8020 Quantitative strategies and algorithmic trading | STAT8020量化策略和算法交易 |
| STAT8021 Big data analytics | STAT8021大数据分析 |
| List C: | 列表C： |
| COMP7308 Introduction to unmanned systems | COMP7308无人系统简介 |
| COMP7309 Quantum computing and artificial intelligence | COMP7309量子计算与人工智能 |
| COMP7409 Machine learning in trading and finance | COMP7409交易和金融领域的机器学习 |
| COMP7502 Image processing and computer vision | COMP7502图像处理与计算机视觉 |
| ARIN7017 Legal issues in artificial intelligence and data science | ARIN7017人工智能和数据科学中的法律问题 |
| *Students who have completed the same or similar courses in their previous studies may, on production of relevant transcripts, be permitted to select up to 18 credits of disciplinary electives from the other two lists if they are not able to find any untaken options from any one of the lists of disciplinary electives. | *在以前的学习中完成了相同或类似课程的学生，如果无法从任何一个学科选修课列表中找到任何未经选择的选项，则在出示相关成绩单后，可以从其他两个列表中选择最多18个学分的学科选修课。 |
| Capstone Requirement (12 credits) | 顶点要求（12学分） |
| ARIN7600 Artificial intelligence project (12 credits) | ARIN7600人工智能项目（12学分） |
