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The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Course Name: Artificial Intelligence
Course Code: COMP 421
I. Basic Course Information
Program(s) on which the course is given: Computer Engineering
Core or elective element of program: Core
Department offering the course: Electrical and Electronics Engineering- Computer Dept
Academic level:4
Semester in which course is offered: Spring
Course pre-requisite(s): Advanced Programming C++ COMP 412
Mathematics III
MATH 203
Credit Hours: 3
Contact Hours Through: 5
Lecture
2.0
Tutorial*
1.0
Practical*
2.0
Total
5.0
Approval date of course specification: September 2013
II. Overall Aims of Course
- Upon completion of this course, students will be able to:
-Have an appreciation for and understanding of both the achievements of AI
and the theory underlying those achievements.
-Have an appreciation for the engineering issues underlying the design of AI
systems.
-Have a basic proficiency in a traditional AI language including an ability to
write simple to intermediate programs and an ability to understand code written in
that language.
-Have an understanding of the basic issues of knowledge representation and
blind and heuristic search, as well as an understanding of other topics such as
minimax, resolution, etc. that play an important role in AI programs.
-Have a basic understanding of some of the more advanced topics of AI such as
learning, natural language processing, agents and robotics, expert systems, and
planning.
III. Program ILOs covered by course
Program Intended Learning Outcomes (By Code)
Knowledge &
Intellectual Skills
Professional Skills
Understanding
General
Skills
1
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
K4, K5, K11, K12
I1, I2 ,I3, I5, I6, I9,
I10
P1, P4, P6
G1, G3, G4
IV. Intended Learning Outcomes of Course (ILOs)
a. Knowledge and Understanding
On completing the course, students should be able to:
k1. Relate practical application of theories in different fields through projects and field
studies.
k2. Express unique oriented Knowledge in the relevant fields.
k3. Recognize principles and methods of design used in electrical and electronic engineering.
k4. Recognize principles and methods of design used in computer engineering.
b. Intellectual/Cognitive Skills
On completing the course, students should be able to:
i1. Use appropriate knowledge and skills to identify, formulate, analyze, and solve complex
engineering problems in order to reach substantiated conclusions.
i2. Use brainstorming and innovation techniques to deal with problems and to develop new
ideas.
i3. Solve and investigate complex problems by methods that include appropriate experiments,
analysis and interpretation of data, and synthesis of information in order to reach valid
conclusions.
i4. Use and develop computer programs.
i5. Apply solutions for complex, open-ended engineering problems.
i6. Apply appropriate computer based methods for modelling and analyzing problems in
electrical and electronic engineering.
i7. Use software engineering techniques in program development.
c. Practical/Professional Skills
On completing the course, students should be able to:
p1. Formulate and use the appropriate mathematical methods for modelling and analyzing
problems in electrical, electronic and communications engineering.
p2. Collect information and develop new ideas.
p3. Design, build and test a communication system.
d. General and Transferable Skills
On completing the course, students should be able to:
g1. Manipulate, sort and present the information in a variety of ways.
g2. Use of general IT tools.
g3. Express creativity and innovation in problem solving and working with limited or
contradictory information.
V. Course Matrix Contents
2
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Main Topics / Chapters
1234567-
Traditional programming
versus Knowledge
engineering
Examples on expert systems
System performance
Human Problem solving
Knowledge representation
Graph analysis, Languages
and tools
Hardware and micro program
control
Development of complete
expert system
Net Teaching Weeks
Duration
(Weeks)
1
Course ILOs Covered by Topic
(By ILO Code)
K&U
I.S.
P.S.
G.S.
k1, k2
1
2
2
i2, i3
k3
2
2
i1
k4
i4
i5
p1
i5, i6
p2
g1
i7
3
All
p3
g2
13
VI. Course Weekly Detailed Topics / hours / ILOs
Week
No.
1
2
3
4
5
6
7
8
9
10
Sub-Topics
Total
Hours
Traditional programming versus
2
Knowledge engineering
Examples on expert systems System
5
performance
Human Problem solving: simulating
Human information , production system
5
as a simulated model, problem solving,
knowledge varieties, kind of experience
Human Problem solving: simulating
Human information , production system
5
as a simulated model, problem solving,
knowledge varieties, kind of experience
Knowledge representation: general look
on knowledge base, knowledge
5
representation strategies
Knowledge representation: general look
on knowledge base, knowledge
5
representation strategies
Midterm Exam
Graph analysis
5
Languages and tools: programming
levels, language tool field, AI languages
5
and environment. Knowledge
engineering tools, expert structures
Hardware and micro program control
5
Contact Hours
Theoretical
Practical
Hours
Hours*
2
2
3
2
3
2
3
2
3
2
3
2
3
2
3
2
3
3
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
11
12
13
14
15
Hardware and micro program control
5
Building of small knowledge system,
Suitable problem choice, original model
5
system development
Development of complete expert system.
Systems evaluation, integration and
5
maintenance.
Development of complete expert system.
Systems evaluation, integration and
5
maintenance.
Final Exam
Total Teaching Hours
2
3
2
3
2
3
2
3
VII. Teaching and Learning Methods
Teaching/Learning
Method
Lectures & Seminars
Tutorials
Computer lab Sessions
Practical lab Work
Reading Materials
Web-site Searches
Research & Reporting
Problem Solving /
Problem-based Learning
Projects
Independent Work
Group Work
Case Studies
Presentations
Simulation Analysis
Course ILOs Covered by Method (By ILO Code)
K&U
All
Intellectual
Skills
All
All
Professional
Skills
All
All
All
All
General
Skills
All
All
Others (Specify):
VIII. Assessment Methods, Schedule and Grade Distribution
Course ILOs Covered by Method
(By ILO Code)
Assessment
Method
K&U
I.S.
P.S.
G.S.
Midterm Exam
Final Exam
Quizzes
Course Work
Report Writing
All
All
All
All
All
All
Week
No.
20 %
All
All
Assessment
Weight /
Percentage
All
10 %
5%
4
The Higher Canadian Institute for Business
and Engineering Technology
Quality Assurance Unit
Course Specification
Case Study
Analysis
Oral
Presentations
Practical
Group Project
Individual Project
All
All
10 %
Others (Specify):
IX. List of References
Essential Text Books
Course notes
Recommended books
Periodicals, Web sites,
etc …
- Artificial Intelligence: A Modern Approach, 2nd edition, by
Russell and Norvig,
Prentice Hall.
- LISPcraft by Robert Wilensky, W.W. Norton.
ISBN #: 0393954420
Course Management System CMS
X. Facilities required for teaching and learning
big sized lecture rooms - computers (Personal & Notebook) - data show
Course coordinator: Associate Professor. Alaa Hamdy
Head of Department: Associate Professor/ Tamer AbdelRahman
Date: September 2013
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