Courses Offered

COMP3270 Artificial Intelligence

2024-25

Instructor(s):

Schnieders Dirk

(Class A)

No. of credit(s):

Gao Shenghua

(Class B)

Recommended Learning Hours:

Lecture:	36.0
Tutorial:	3.0

Pre-requisite(s):

COMP2119 or COMP2502 or FITE2000

Co-requisite(s):

Mutually exclusive with:

ELEC4544 or IIMT3688

Remarks:

Course Learning Outcomes

1.	[1] understand the basic principles and technologies of intelligent computer systems
2.	[2] explain the algorithms to achieve AI
3.	[3] develop some AI programs

Mapping from Course Learning Outcomes to Programme Learning Outcomes
	PLO a	PLO c	PLO j
CLO 1	T,P	T,P
CLO 2	T	T
CLO 3		P	P

T - Teach, P - Practice
For BEng(CompSc) Programme Learning Outcomes, please refer to here.

Syllabus

Calendar Entry:
This is an introduction course on the subject of artificial intelligence. Topics include: intelligent agents; search techniques for problem solving; knowledge representation; logical inference; reasoning under uncertainty; statistical models and machine learning.

Detailed Description:

Basic principles	Mapped to CLOs
Intelligent agents, agents and environments, concept of rationality	1
AI algorithms	Mapped to CLOs
Search techniques and problem solving	2
Logical, uncertain knowledge and reasoning	Mapped to CLOs
Logical knowledge and reasoning	2
Applications	Mapped to CLOs
Application programming	3

Assessment:
Written Examination: 50%
Continuous Assessment: 50%

Teaching Plan

Please refer to the corresponding Moodle course.

Moodle Course(s)

Courses Offered

COMP3270 Artificial Intelligence

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