本课程旨在培育学生掌握数据分析与人工智慧领域的前沿方法与技能。学生透过学习这些专业能力，将业务需求有效转化为资讯科技领域的解决方案。
本课程分为两部分－必修科目 (共 14 学分) 及选修科目 (共 15 学分)。
选修科目分为 (i) 数据分析，(ii) 人工智能, 和 (iii) 硕士专题专案及研究，学生可以自由选读任何选修科。
| 学分 | 学分 | |
|---|---|---|
| 必修科目 | 14 | |
| Artificial Intelligence | 3 | |
| Python for Data Analytics and Artificial Intelligence | 3 | |
| Quantitative Methods for Data Analytics and Artificial Intelligence | 3 | |
| Principles and Practices of Data Analytics | 3 | |
| IT Forum | 1 | |
| Ethics of Data Analytics and Artificial Intelligence | 1 | |
| 选修科目 | 15 | |
| 专业一：数据分析 | ||
| Innovative Laboratory | 3 | |
| Data Security and Privacy | 3 | |
| Blockchain and Cryptocurrenciesx | 3 | |
| Special Topics in Data Analytics | 3 | |
| Financial Technology | 3 | |
| Database Systems and Administration | 3 | |
| Data Mining and Knowledge Discovery | 3 | |
| Business Intelligence | 3 | |
| Visual Analytics and Decision Support | 3 | |
| Big Data Analytics | 3 | |
| Cloud Computing | 3 | |
| Audio and Speech Processing | 3 | |
| 专业二：人工智能 | ||
| Natural Language Processing and Large Language Models | 3 | |
| Computer Vision | 3 | |
| Innovative Laboratory | 3 | |
| Prompt Engineering for Generative AI | 3 | |
| Blockchain and Cryptocurrencies | 3 | |
| Special Topics in Artificial Intelligence | 3 | |
| Recommender Systems | 3 | |
| Machine Learning | 3 | |
| Web Intelligence and Its Applications | 3 | |
| Data Mining and Knowledge Discovery | 3 | |
| Business Intelligence | 3 | |
| Audio and Speech Processing | 3 | |
| Autonomous Robotics | 3 | |
| 硕士专题专案及研究 | ||
| MSc Practicum | 3 | |
| MSc Research I | 3 | |
| MSc Research II | 3 | |
| 29 | ||
备注：教学课程可能会有少许修改。
同学可以选择一年全日制或两年兼读制的学习模式。大部分科目将于平日晚上6:30-9:20举行，小部分科目、考核活动和补课或会在星期六日间举行，以方便全日制及兼读制的学生出席。
全日制学生的课程安排如下：
| 上学期 学分 | 下学期 学分 | |
|---|---|---|
| 第一年 | ||
| Python for Data Analytics and Artificial Intelligence | 3 | |
| Principles and Practices of Data Analytics | 3 | |
| Artificial Intelligence | 3 | |
| Quantitative Methods for Data Analytics and Artificial Intelligence | 3 | |
| Ethics of Data Analytics and Artificial Intelligence | 1 | |
| IT Forum | 1 | |
| Elective Courses | 15 |
兼读制学生的课程安排如下：
| 上学期 学分 | 下学期 学分 | |
|---|---|---|
| 第一年 | ||
| Principles and Practices of Data Analytics | 3 | |
| Quantitative Methods for Data Analytics and Artificial Intelligence | 3 | |
| Ethics of Data Analytics and Artificial Intelligence | 1 | |
| Elective Courses | 9 | |
| 第二年 | ||
| Python for Data Analytics and Artificial Intelligence | 3 | |
| Artificial Intelligence | 3 | |
| IT Forum | 1 | |
| Elective Courses | 6 |
授课语言为英语，所有教材都是以英语编写。