CS4486 Intelligent Systems

Part I

Course Duration: One Semester

Credit Units: 3

Level: B4

Medium of Instruction: English

Pre-requisites:Nil

Pre-cursors:
CS2302 Data Structures and Algorithms /or
CS2468 Data Structures and Data Management /or
CS3334 Data Structures

Equivalent Courses: Nil

Exclusive Courses: Nil

Part II

Course Aims:
This course aims to equip students with the skills of problem solving using artificial intelligence (AI) techniques through a demonstrable knowledge in a range problem solving methods and the associated knowledge representation and machine learning techniques.

Course Intended Learning Outcomes (CILOs):
(state what the student is expected to be able to do at the end of the course according to a given standard of performance)

Upon successful completion of this course, students should be able to:
 

No.	CILOs	Weighting (if applicable)
1.	demonstrate knowledge of the fundamental principles intelligent systems;
2.	distinguish between conventional computer applications and intelligent applications;
3.	analyze and compare the relative merits of a variety of AI problem solving techniques;
4.	formulate and analyse intelligent system problems;
5.	design and implement intelligent problem solving methods.

Teaching and Learning Activities (TLAs):
(Indicative of likely activities and tasks designed to facilitate students’ achievement of the CILOs. Final details will be provided to students in their first week of attendance in this course)

Teaching pattern:
Suggested lecture/tutorial/laboratory mix: 2 hrs. lecture; 1 hr. tutorial.
 

CILO No.	TLAs	Hours/week (if applicable)
CILO 1 -CILO 5	The course will consist of a balance-mixed of theory and practice. Through a combination of formal lectures and coursework, the students will become able to apply major AI concepts and problem solving approaches to solving real life problems. The coursework will consist of a programming assignment that involves implementing AI algorithms using a high level language such as Java or C to solve a specific AI problem.

Assessment Tasks/Activities:
(Indicative of likely activities and tasks designed to assess how well the students achieve the CILOs. Final details will be provided to students in their first week of attendance in this course)

The course ILOs are assessed using the following approaches:
 

CILO No.	Type of Assessment Tasks/Activities	Weighting(if applicable)	Remarks
CILO 1,CILO 2	ILO 1 and 2 will be assessed mainly through examination that aims to assess the depth of understanding on a range of AI concepts and techniques.
CILO 4,CILO 5	ILO 4 and 5 will be assessed through coursework for which the students have to demonstrate practical as well as analytical skills to select implement and evaluate the effectiveness and efficiency of the chosen AI techniques and approaches to solving a specific AI problem.
CILO 3	ILO 3 will be assessed through a combination of examination and coursework.

Grading of Student Achievement:
Examination duration:  2 hours
Percentage of coursework, examination, etc.:  30% CW; 70% Exam
Grading pattern: Standard (A+AA-…F)
For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.

Part III

Keyword Syllabus:
Artificial intelligence. State space search. Heuristic search, Knowledge representations. Rule-based systems, Stocastic search algorithms, Logical inference, Uncertainy reasoning methods, Machine Learning, Decision trees.