List of Courses

Information
Description
Outcomes
Contents
Methodologies
Assessment
Books

Artificial Intelligence

Course Code :
CS341
Level :
Undergraduate
Course Hours :
3.00 Hours
Department :
Department of Information Systems

Instructor information :

Area of Study :

Use and adopt fundamental and advanced mathematics, basic sciences and computer science theories in all development phases of knowledge Base Systems. Understand knowledge that enhances skills in analyzing and interpreting knowledge in Artificial Intelligence area. Evaluate effectively the merits of Artificial Intelligence Science using appropriate analytical skills. Comprehend deeply the basic concepts of computer science to be ready for further and continuous learning in field of Artificial Intelligence

For further information :

Telephone: 16383 (16FUE)
E-mail: [email protected]

Artificial Intelligence

Knowledge Representations: Predicate Calculus, Structured Representations, Network Representations. State Space Search: trees and graphs, heuristic search, model based reasoning, case-based reasoning, reasoning with uncertain or incomplete knowledge. Overview of AI languages, Overview of AI Application Areas. In particular, we consider the use of Prolog for database querying, parsing, meta-programming, and problem solving in AI. The programming assignments can be coded in SWI_Prolog or XSB

For further information :

Telephone: 16383 (16FUE)
E-mail: [email protected]

Artificial Intelligence

NAQAAABET

Course outcomes:

a. Knowledge and Understanding:

1-	Describe the fundamental mathematical logic to solve problems in AI field
2-	Explain different qualitative and quantitative methods for knowledge analysis
3-	Define the principles and techniques of different Artificial Intelligence areas

b. Intellectual Skills:

1-	Identify main ideas, patterns, components, attributes and detect relationships between these components in the field of Artificial Intelligence.
2-	Select appropriate methodologies and techniques for a given problem solution and setting out their limitations, restrictions and errors in the field of Artificial Intelligence
3-	Evaluate and justify different solutions using well-defined criteria in the field of Artificial Intelligence.

c. Professional and Practical Skills:

1-	Analyze, Design, Implement and test Knowledge Based Systems
2-	Apply, design methodologies, AI programming languages and different supporting tools to develop Knowledge base systems
3-	Deploy effective supporting tools to develop and document of Knowledge base systems

d. General and Transferable Skills:

1-	Work in a team to develop the requirement documentation
2-	Apply communication skills in presentations and report writing using various methods and tools.

For further information :

Telephone: 16383 (16FUE)
E-mail: [email protected]

Artificial Intelligence

Course topics and contents:

Topic	No. of hours	Lecture	Tutorial/Practical
Introduction to AI Concepts	4	2	2
Introduction to AI Concepts	4	2	2
Problems and Problem space	4	2	2
Problem Characteristics	4	2	2
Problem Characteristics	4	2	2
AI-Search	4	2	2
AI-Search	4	2	2
Knowledge Acquisition	4	2	2
Mid Term	2
Knowledge Acquisition	4	2	2
Knowledge representation	4	2	2
Geometric analogy net	4	2	2
Recording Cases	4	2	2
Final Exam	2

For further information :

Telephone: 16383 (16FUE)
E-mail: [email protected]

Artificial Intelligence

Teaching And Learning Methodologies:

Teaching and learning methods
Interactive Lectures including discussion
Practical Lab Sessions
Self-Study (Project / Reading Materials / Online Material / Presentations)
Problem Solving

For further information :

Telephone: 16383 (16FUE)
E-mail: [email protected]

Artificial Intelligence

Course Assessment :

Methods of assessment	Relative weight %	Week No.
Assignments	10.00
Final Exam	40.00	14
Midterm Exam (s)	20.00	9
Others (Participation)	10.00
Quizzes	10.00	5
Team Work Projects	10.00

For further information :

Telephone: 16383 (16FUE)
E-mail: [email protected]

Artificial Intelligence

Books:

Book	Author	Publisher

Course notes :

Course Notes are available with all the slides used in lectures in electronic form on Learning Management System (Moodle)

Recommended books :

Ivan Bratko, Prolog: programming for artificial intelligent, Addison Wesley, , (last edition).

Web Sites :

•IEEE intelligent systems & their applications •IEEE transactions on pattern analysis and machine intelligence •Intelligence : new visions of AI in practiceinternational journal of robotics & automationAI magazine •Technological Innovations Artificial Intelligence Periodical •www.ekb.eg •www.ai.com •www.robotics.com