|
| 1.
| understand the basics and general frameworks of the common AI approaches (e.g., search, machine learning, deep learning) for problem solving |
| 2.
| understand the workflow, the capabilities and the limitations of some state-of-the-art AI technologies, platforms and tools for solving data intensive problems with AI approaches |
| 3.
| identify potential AI-oriented tasks in a problem; design and implement AI pipelines properly in solving the corresponding tasks |
| 4.
| carry out AI experimentation with justifiable processes and evaluation; analyze and address potential issues arising from the experimentation |
Mapping from Course Learning Outcomes to Programme Learning Outcomes
| | PLO a | PLO b | PLO c | PLO d | PLO e | PLO f | PLO g | PLO h | PLO i | PLO j |
| CLO 1 | T | T | | | | T | | T | T | |
| CLO 2 | T | T | | | | | | | T | T |
| CLO 3 | | T | T | T | T | T | T | T | | T |
| CLO 4 | | | T | T | T | | T | T | | T |
T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to
here.
|
| Syllabus |
|
Calendar Entry:
|
|
Detailed Description:
| Self-Paced Learning |
Mapped to CLOs
|
| Introduction to AI methodologies and the experimentation cycle | 1, 2 |
| Selected state-of-the-art AI platforms & tools | 1, 2 |
| Project |
Mapped to CLOs
|
| Problem Identification | 1, 2, 3 |
| Implementation | 1, 2, 3, 4 |
| Demonstration & Presentation | 1, 2, 3, 4 |
|
|
Assessment:
Continuous Assessment:
100%
|
| Teaching Plan |
|
Please refer to the corresponding Moodle course.
|
| Moodle Course(s) |
|
|
