| Course code | AIST4999 |
| Course title | Final Year Project II 畢業專題研究﹝二﹞ |
| Course description | The course is designed to provide students with an opportunity to carry out, under the supervision of an academic staff, an independent project with research elements in artificial intelligence topics. 在導師指導下，學生將進行一個關於人工智能的獨立研究項目。 |
| Unit(s) | 3 |
| Course level | Undergraduate |
| Semester | 2 |
| Pre-requisites | AIST4998 / ESTR4998 |
| Exclusion | ESTR4999 |
| Grading basis | Graded |
| Grade Descriptors | A/A-: EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions. B+/B/B-: GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered. C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems. D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems. F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course. |
| Learning outcomes | 1. Be able to identify and have a basic understanding of the literature related to the project topic. 2. Be able to define and complete a project that utilizes results in the literature. 3. Be able to perform a critical review of the project. 4. Develop technical writing skills. |
| Assessment | Essay Presentation |
| Recommended Reading List | Literature review materials will be recommended by the project supervisor. |
| AISTN programme learning outcomes | Course mapping |
| Upon completion of their studies, students will be able to: | |
| 1. identify, formulate and solve AI-related engineering problems (K/S); | Y |
| 2. design a system, component, or process to meet desired needs within realistic constraints, such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability (K/S/V); |
Y |
| 3. understand the impact of AI solutions in a global and societal context, especially the importance of health, safety and environmental considerations to both workers and the general public (K/V); | Y |
| 4. communicate and work effectively in multi-disciplinary teams (S/V); |
Y |
| 5. apply knowledge of mathematics, science, and engineering appropriate to the AI degree discipline (K/S); |
Y |
| 6. design and conduct experiments, as well as to analyze and interpret massive data (K/S); | Y |
| 7. use the techniques, skills, and modern computing tools necessary for engineering practice appropriate to the AI and computing discipline (K/S); | Y |
| 8. understand professional and ethical responsibility (K/V); and | Y |
| 9. recognize the need for and the importance of life-long learning (V). |
Y |
| Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes | |