|Course title||Final Year Project II
|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.
|Pre-requisites||AIST4998 / ESTR4998|
|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.
|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);
|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);
|5. apply knowledge of mathematics, science, and engineering appropriate to the AI degree discipline (K/S);
|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).
|Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes|