3. Programme Study Plan 

Table 1 Basic compulsory courses 

Course	Type	Class Time	Credit
Introduction to Data Science	Compulsory	45	3
Time Series Analytics	Compulsory	45	3

Table 2 Core Compulsory majors 

Course	Type	Class Time	Credit
Hadoop Fundamentals for Big Data Processing and Applications	Compulsory	45	3

Table 3 Elective courses (take six courses from the following courses) 

Course	Type	Class Time	Credit
Data Analytics and Statistical Inference	Elective	45	3
An Introduction to Big Data Programming	Elective	45	3
Cloud Computing and Big Data Analytics	Elective	45	3
Parallel Computing	Elective	45	3
Artificial Neural Networks	Elective	45	3
Big Data Analytics and Applications	Elective	45	3
Special Topic for Education Big Data	Elective	45	3
Special Topic for Financial Market Data Analytics and Data Mining	Elective	45	3
Special Topic for the Accurate Marketing of the Era of Big Data	Elective	45	3

Table 4 Others 

Course	Type	Class Time	Credit
Special Academic Topics	Compulsory	N/A	1

Table 5 Dissertation Writing 

Course	Type	Class Time	Credit
Thesis Writing	Compulsory	N/A	9

Illustration 

1. During their programme, students must complete the basic and core compulsory credits, elective credits and various training requirements specified in the programme, and obtain 37 credits. The specific distribution is as follows: a total of 6 credits for the basic compulsory courses in Table 1; the core compulsory courses in Table 2. A total of 3 credits; a total of 9 elective courses in Table 3, students choose 6 from them, a total of 18 credits; participate in academic activities recognized by the academic committee of the faculty at least 5 times, a total of 1 credit; thesis writing total 9 credits. 
2. The specific course arrangement in the student's personal training plan is determined by the supervisor and the student based on the professional scope and research direction. 
3. After completing the compulsory and elective courses, student can start writing thesis, project report and proposal reports. After the proposal report is approved, student can start writing thesis and project design report.  
4. Students must publish or have at least one paper published or accepted in an academic journal recognized by City University of Macau during their master’s degree programme; (Updated on September 1, 2023) 

During the master's studies, students should at least have a paper published or accepted in the academic journals or conferences recognized by City University of Macau. One of the following requirements should be fulfilled:

• SCI  Journal or
• EI Journal or
• EI-indexed conferences (included in IEEE Xplore, the ACM Digital Library, or SpringerLink); or
• The 120 journals listed in categories N/Q and T/X of Peking University's A Guide to the Core Journals of China (Chinese core general sci-tech journals); or 
• International academic conference or journal recommended by the China Computer Federation (CCF), or in the Chinese scientific and technological journals catalogue recommended by CCF; or 
• At least one invention patent application (domestic or international) formally accepted during the studies.

  Note: 

1. In principle, students should be the first author of the paper. If the student is the second author, the advisor should be the first author.

2. All published articles and accepted patent applications submitted in support of the master's graduation application should be related to the thesis research, and City University of Macau should be the first author's affiliation.

3. Students should submit official proof, such as an acceptance email or an acceptance letter, of paper acceptance or patent application acceptance; the faculty will review whether the requirements are met.

4. Invention patent applications must comply with the University's intellectual property management regulations. For details, please consult the advisor or the Knowledge Transfer and Transformation Center.

5. The above constitute the basic requirements set by the faculty.

5. If student pass the dissertation oral defense, obtain a total of 37 credits, and do not violate the relevant regulations of the university, student can apply for the award of requirements degree in accordance with the master application procedures of the City University of Macau. 

Study Plan Course Framework	Programme Credit
Basic compulsory courses	6
Core compulsory for majors	3
Electives	18
Special Academic Topics	1
Thesis	9
Total credits	37

Note: The teaching language is Chinese/English 

 

4. Teaching requirements 

1. Students are required to complete 3 compulsory courses and 6 elective courses during the study period and sit for the examinations. and those who pass the courses will be awarded credits for the courses, totaling 27 credits. Participate in academic activities and special research recognized by the academic committee of the faculty at least 5 times, totaling 1 credit. (Note: "Special Academic Topics" is a year-long course)

2. After completing the required and elective courses, student can start writing the proposal report and graduation thesis. If student pass the dissertation oral defense, obtain a total of 37 credits, and do not violate the relevant regulations of the university, student can apply for the award of master degree in accordance with the master application procedures of the City University of Macau.   

 

5. Admission criteria 

Applicants must have a bachelor's degree or equivalent. Priority will be given to those with pre-requisite academic qualifications in computer science, data analysis, data management, information science, mathematics, statistics, machine learning, statistics, machine learning, data mining, database and other fields and related majors. Applicants are required to take the entrance examination organized by City University of Macau and will be admitted on the basis of merit.