| Course code | AIST2602 |
| Course title | Engineering Practicum 工程實務 |
| Course description | This course arranges industrial and professional workshops or seminars as required by the Major programme. 本科安排主修科目要求的工業和專業工作坊或講座。 |
| Unit(s) | 1 |
| Course level | Undergraduate |
| Semester | 2 |
| Exclusion | CSCI3250 or CSCI3251 or ENGG2601 or ENGG2602 |
| Grading basis | Pass / Fail |
| Grade Descriptors | P – (Ungraded Pass): Performance meets, exceeds or far exceeds expectation in relevant measurement dimensions; Overall level of competence: Moderate to High; U – (Failure): Performance does not meet expectation in most relevant measurement dimensions; Overall level of competence: Not reaching the basic standard. |
| Learning outcomes | At the end of the course of studies, students will have acquired the ability to 1. Hand-on skills of engineering practice 2. Understanding the value of practical engineering skills and experiences |
| Assessment | Others: 100% |
| Recommended Reading List | 1. E.A. Stephan et al., Thinking like an engineer: an active learning approach, Pearson Prentice Hall, 3rd ed, 2015. 2. The Hong Kong Institution of Engineers web site (https://www.hkie.org.hk). 3. Intellectual Property Department web site (https://www.ipd.gov.hk). 4. The Office of the Government Chief Information Officer (OGCIO) web site (https://www.ogcio.gov.hk). |
| AISTN programme learning outcomes | Course mapping |
| Upon completion of their studies, students will be able to: | |
| 1. apply knowledge of mathematics, science, and engineering appropriate to the AI degree discipline (K/S); | |
| 2. design and conduct experiments, as well as to analyze and interpret massive data (K/S); |
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| 3. 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); | |
| 4. identify, formulate and solve AI-related engineering problems (K/S); |
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| 5. understand professional and ethical responsibility (K/V); |
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| 6. communicate and work effectively in multi-disciplinary teams (S/V); | |
| 7. 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); | |
| 8. recognize the need for and the importance of life-long learning (V); and | |
| 9. use the techniques, skills, and modern computing tools necessary for engineering practice appropriate to the AI and computing discipline (K/S). |
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| Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes | |