Bachelor of Science in Artificial Intelligence
Awarding Institution | Macao Polytechnic University |
---|---|
Host Academic Unit | Faculty of Applied Sciences |
Partner Teaching Academic Unit(s) (if any) | - |
Programme Registration Code | UP-N13-L60-2323Z-11 |
University Programme Code | 4LAIDI |
Final Award (FHEQ Level of Study) | 6 |
Number of Credits Required for Graduation | 126 |
Normal Period of Study | 4 |
Medium of Instruction | English |
Specialisation(s) | - |
Professional Accreditation | - |
Partner Teaching Institution(s) (if any) | - |
PROGRAMME OBJECTIVES
The evolving field of Artificial Intelligence (AI) has driven breakthrough changes across a wide variety of industries such as information technology, manufacturing, finance, agriculture, health care, retail, and entertainment. AI has been identified as the key technology for future digital economy in China and around the world. Macao Polytechnic University has a solid foundation in AI teaching and research and will adopt the existing academic-accredited student support system and the time-tested quality assurance processes of the University. Students are able to explore areas including Image and video processing; Natural Language Processing; Automatic Speech Recognition; Big Data Analysis; AI driven drug discovery etc. This helps students to enhance their knowledge of modern technologies and recent advancements in artificial intelligence, determine the topic for their research project and area of interest for subsequent professional development including AI system design and development in Internet enterprises, AI-powered industries, government agencies as well as further studies in relevant Master and PhD programmes.
PROGRAMME INTENDED LEARNING OUTCOMES (PILOS)
Knowledge and Understanding
On completion of this programme, students will be able to demonstrate understanding of:
PILO-1. | Select and apply proven methods, tools and techniques to the effective and efficient implementation of information systems on common platforms, including the Internet platform. |
PILO-2. | Acquire essential knowledge in specific fields of artificial intelligence, including machine learning, computer vision and natural language processing. |
PILO-3. | Apply necessary mathematical techniques to model, analyse and devise solutions to complex problems. |
PILO-4. | Work independently to develop an understanding of, and the knowledge and skills associated with the general support and mitigation of security risks of computer systems and networks. |
Skills and Attributes
On completion of this programme, students will be able to:
PILO-5. | Design and implement both relational and non-relational data stores, with an emphasis on how to organise, maintain, retrieve and analyse information. |
PILO-6. | Distinguish the fundamental and operational issues of computer systems and artificial intelligence applications, with considerations of user, business, ethical, societal and environmental needs. |
PILO-7. | Evaluate, prepare and communicate effectively on technical information to both technical and non-technical audience. |
PILO-8. | Work as an effective member of a team in the analysis, design and development of software systems, with recognition of requirement to support equality, diversity and inclusion. |
PILO-9. | Use project planning, risk management and quality management techniques in solutions to complex problems. |
PILO-10. | Build the capacity and desire for lifelong learning and to learn advanced and emerging technologies on one's own. |
By attaining these PILOs, students will have attained the graduate attributes of the University as demonstrated below:
Graduate Attributes | PILOs | |||||||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
To demonstrate strong academic competence in relevant disciplines | ✓ | ✓ | ✓ | ✓ | ✓ | |||||
To think critically and to contribute constructively in teamwork and leadership | ✓ | ✓ | ||||||||
To communicate effectively both verbally and in writing | ✓ | |||||||||
To possess a global vision which enables them to understand issues and problems from different perspectives | ✓ | ✓ | ||||||||
To articulate effectively in a variety of contexts using knowledge, skills and expertise acquired to serve both the local and international community | ✓ | |||||||||
To have a positive attitude towards society and environment in the development of a fair and caring society | ✓ | |||||||||
To demonstrate a keen interest in and strong capacity for life-long learning | ✓ | |||||||||
To practise high standards of ethical behaviour | ✓ |
TEACHING AND LEARNING
In this programme, students will work towards attaining the PILOs through the following teaching and learning activities:
PILOs | Teaching and Learning Activities |
Knowledge and understanding | 1. Lectures in classroom |
Skills and Attributes | 1. Practical exercises in laboratory |
ASSESSMENT
In this programme, students will receive assessment activities of the following types in order to assess whether they are able to attain the stated PILOs.
PILOs | Types of Assessment Activities |
Knowledge and understanding | 1. Written test and examination |
Skills and Attributes | 1. Assignment |
2. Project | |
3. Presentation |
The assessment will be conducted following the University’s Assessment Strategy.
PROGRAMME STRUCTURE
Year | Study Focus | Learning Modules | ||
---|---|---|---|---|
Code | Title | Type | ||
1 | Fundamental year (Learning the fundamental knowledge in problem solving and programming skills) | COMP1121 | Introduction to Computer Science and its Application | Compulsory |
COMP1122 | Introduction to Programming | Compulsory | ||
MATH1111 | Linear Algebra | Compulsory | ||
MATH1112 | Calculus | Compulsory | ||
MENG1111 | English I | Compulsory | ||
LLAW1120 | Constitution and Basic Law | Compulsory | ||
COMP1123 | Computer Organization | Compulsory | ||
COMP1124 | Advanced Programming | Compulsory | ||
COMP1125 | Introduction to E-Business | Compulsory | ||
MATH1113 | Discrete Mathematics | Compulsory | ||
MENG1112 | English II | Compulsory | ||
HIST1120 | Chinese History and Culture | Compulsory | ||
2 |
Broadening year (Accumulating more knowledge in computing and AI at an intermediate level) |
COMP2111 | Database Design | Compulsory |
COMP2112 | Data Structures and Algorithms | Compulsory | ||
COMP2113 | Operating Systems | Compulsory | ||
CSAI2121 | Probability and Statistics | Compulsory | ||
MENG2111 | English III | Compulsory | ||
CSAI2122 | Introduction to Artificial Intelligence | Compulsory | ||
SOCI1112 | Social Sustainable Development | Compulsory | ||
COMP2114 | Ethics and Professional Issues in Computing | Compulsory | ||
COMP2115 | Web Design and Development | Compulsory | ||
COMP2116 | Software Engineering | Compulsory | ||
CSAI2123 | Introduction to Data Science | Compulsory | ||
MENG2112 | English IV | Compulsory | ||
3 | Strengthening year (Strengthening students’ skills in more advanced topics in AI and system development) | COMP3111 | Advanced Web Development | Compulsory |
COMP3112 | Project Management | Compulsory | ||
MENG3111 | Science Communications | Compulsory | ||
CSAI3121 | Machine Learning and Intelligent Data Analysis | Compulsory | ||
CSAI3122 | Natural Language Processing | Compulsory | ||
CSAI3123 | Neural Networks and Deep Learning | Compulsory | ||
CSAI3124 | Artificial Intelligence Application Project | Compulsory | ||
CSAI3125 | Computer Networks | Compulsory | ||
General Elective (I) | Elective | |||
Major Elective (I) | Elective | |||
4 | Advance year (Enhancing students’ theoretical thinking and to cover more advanced AI topics) | COMP4111 | Computer Security | Compulsory |
CSAI4121 | Human Factors and User Interfaces | Compulsory | ||
CSAI4299 | Final Year Project | Compulsory | ||
General Elective (II) | Elective | |||
Major Elective (II) | Elective | |||
Major Elective (III) | Elective | |||
3/4 | General Elective Modules to enhance students’ vision | CSAI0124 | Introduction to Linguistics | Elective |
CSAI0125 | Introduction to Translation Studies | Elective | ||
COMP4115 | Selected Topics in Smart Tourism | Elective | ||
MSEL3101 | Introduction to Psychology | Elective | ||
MSEL3102 | Introduction to Sociology | Elective | ||
MSEL3103 | Introduction to Economics and Finance | Elective | ||
MSEL3105 | Introduction to Marketing | Elective | ||
MSEL3107 | Interpersonal Relations | Elective | ||
MSEL3108 | Accounting | Elective | ||
MSEL3110 | E-Government | Elective | ||
MSEL3111 | Special Topics I | Elective | ||
MSEL3112 | Special Topics II | Elective | ||
MSEL3113 | Technology on Language Learning and Teaching | Elective | ||
MSEL3114 | Graphics Design | Elective | ||
3/4 | Major Elective Modules in advanced AI topics | CSAI0111 | Expert Systems | Elective |
CSAI0112 | Computer Vision and Imaging | Elective | ||
CSAI0113 | Advanced Topics in Machine Translation | Elective | ||
CSAI0114 | Speech Recognition Technology and Application | Elective | ||
CSAI0115 | Data Mining Technology and Application | Elective | ||
CSAI0116 | A.I. Driven Drug Discovery and Development | Elective | ||
CSAI0117 | Advanced Topics in A.I. I | Elective | ||
CSAI0118 | Advanced Topics in A.I. II | Elective | ||
CSAI0119 | High-performance and Parallel Computing | Elective | ||
CSAI0120 | Domain Specific Languages | Elective | ||
CSAI0121 | Theory of Computation | Elective | ||
CSAI0122 | Graphics and Virtual Environments | Elective | ||
CSAI0123 | Numerical Optimization | Elective | ||
COMP4116 | Digital Image and Multimedia Processing | Elective | ||
COMP4119 | Mobile Computing and Wireless Networks | Elective | ||
COMP4127 | Internship | Elective | ||
COMP4128 | Text Corpus Technology and Application | Elective | ||
COMP4129 | Introduction to Internet-of-Things | Elective | ||
COMP4130 | Introduction to Big Data | Elective | ||
COMP4131 | E-commerce with Big Data | Elective | ||
COMP4132 | Cloud Computing | Elective |
ENTRY REQUIREMENTS
The entry requirements are defined in the University’s Academic Regulations Governing Bachelor’s Degree Programmes. An applicant shall be considered for admission if s/he:
- holds a qualification not lower than Grade 12 or the equivalent, and
- fulfils other programme-specific admission criteria.
An applicant of age 23 or above, proven to possess relevant capabilities (especially in the entrance examination(s) of the University), shall be considered for admission to a bachelor’s degree programme with a waiver on the qualification requirement stated above.
More details about admission are available here.
STUDENT FEEDBACK
Each student is allocated a year tutor who provides general academic and pastoral support throughout the whole period of study. Year tutors are the first point of contact in matters stated above. Various communication channels are available for students to express their opinions and suggestions, such as via their respective year tutors, student representatives, programme coordinators and assistant programme coordinators, and dialogue meetings at different levels. The dialogue meetings serve as platforms for consultation and discussion between students and respective personnel ranging from the programme, the faculty, the academic support and administrative units, to the university management. Feedback is made by respective personnel to every issue raised by the students during the meeting with follow-up actions tracked. Student surveys are conducted in every learning module on a semesterly basis to collect students’ opinions regarding the delivery of the modules. User satisfaction surveys are conducted annually on central student services. Feedback collected via these surveys will be followed up by the academic units or respective departments.
STUDENT SUPPORT
Students will receive an orientation about their four years of study at the beginning of the first year. Year tutors are appointed to individual students upon admission to provide academic and pastoral support throughout the period of study in the programme. Students may seek academic advices from their year tutors or programme coordinators regarding their learning path/plan and registration of learning modules.
In individual learning modules, the instructors’ office hours and contact information are made accessible to students for any questions regarding their study. Students’ learning engagement and performance will be reviewed on a regular basis by year tutors and programme coordinators to identify learning needs and provide relevant support. Students’ learning performance and progression will also be reviewed by the programme examination board to ensure their learning is adequately supported and their progress is on track.
Counselling services, careers services and student support services are accessible to all students through the Student Affairs Office. A wide variety of extracurricular activities (e.g. seminars, workshops, exchange opportunities, fieldtrips etc.) are available via the Student Affairs Office. Students may make full use of the variety of learning oppportunities, both curricular and extracurricular, to develop their academic and holistic capabilities for their future careers or further studies.
SUPPORT FOR STUDENTS WITH DISABILITIES
A university-wide policy is in place to ensure that all student needs are taken care of and a supportive and accessible learning environment is maintained. When cases of special needs are notified or identified, special arrangements are made on a case-by-case basis with the joint effort of the programme and various student support services of the University, such as the Registry, the Student Affairs Office, the Information Technology Department and the Campus Management and Development Department, etc. to provide the necessary support.
ADDITIONAL RELEVANT INFORMATION
Graduates from the Programme will have developed a range of cognitive and practical skills together which will be applicable to different context beyond academia. To broaden the participation of students in their communication with the global Computing and AI community, the Programme promotes internship, joint student projects with organisations, student activities, and overseas exchanges. Throughout the academic year, the Programme also invites external speakers to share their experience with our students, by giving seminars or teaching practical modules. Moreover, the Programme also organises short training modules, provided by leading local companies, for our students. Industrial Advisory Meeting organised by the Programme is held at least annually to provide the Programme with valuable industrial advice and feedbacks on the performance of our graduates.