Minor in Data Analytics and Artificial Intelligence

General Information

The Minor in Data Analytics and Artificial Intelligence (DAAI) programme aims to train students from different disciplines to be able to understand and apply the data driven approach and AI technologies (e.g., machine learning, natural language processing, data mining) to solve problems and innovate for new opportunities in different disciplines.

The programme is co-offered by Department of Computer Science and Department of Mathematics. All undergraduate students, except (i) students from Department of Computer Science; or (ii) students from Department of Mathematics; or (iii) students from Data and Media Communication concentration of Journalism, are eligible to pursue the study of the minor programme. Students are required to take three Required Courses to acquire basic skills and knowledge needed for DAAI and two DAAI related Elective Courses, with at least one course at Level 3 or 4. Please note that no registration priority will be given to enrolment in minor courses. Upon completion of five courses required for the minor programme, students should apply to the Academic Registry for approval.

Requirements

THREE Required Courses:

Course Code	Course Title	Units	Offered in 2025-2026
			Sem. 1	Sem. 2
COMP1007 OR COMP1016	Introduction to Python and Its Applications OR Mathematical Methods for Business Computing	3	✓	✓
ITEC1007 OR ITEC2025#	Getting Started with Artificial Intelligence OR AI and Data Analytics for Health and Social Innovation I#	3		✓
ITEC2026^	Fundamental of Data Analysis and Management^	3	✓
Total:		9

Any TWO of the Following Elective Courses^*:

Course Code	Course Title	Units	Offered in 2025-2026
			Sem. 1	Sem. 2
COMP3057	Introduction to Artificial Intelligence and Machine Learning	3	✓
COMP3065	Artificial Intelligence Application Development	3		✓
COMP3115	Exploratory Data Analysis and Visualization	3		✓
COMP4015	Artificial Intelligence and Machine Learning	3
COMP4085	Selected Topics in Intelligent Informatics	3
COMP4125	Visual Analytics	3
COMP4135	Recommender Systems and Applications	3		✓
COMP4136	Natural Language Processing and Large Language Models	3	✓
COMP4137	Blockchain Technology and Applications	3		✓
ITEC2016	Data-driven Visualization for the Web	3
ITEC3015	Web Development for Data Storytellers	3		✓
MATH3626	Computational Statistics for Data Science	3
MATH3836	Data Mining	3	✓
Total:		6

---

^* Students are required to take at least one elective course at Level 3 or 4; Students must fulfill the prerequisites or obtain approval from the instructors before they can enroll these courses.

For further information, please e-mail to .

^# The course was offered using COMP2035 course code before 2025/26 Semester 2. (The re-title is subject to university approval.)
^{^} The course was offered using COMP2865 course code before 2025/26 Semester 2. (The re-title is subject to university approval.)