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EEM   600   Principles of Artificial Intelligence


Office Hours :  Any time, please send an e-mail to :

Office No:       14-146

Office Location:  College of Engineering, Building 14.

Office Telephone:  ++ 973 17876286,  or  ++ 973 17876606

Welcome to the Course:
Master of Science in Artificial Intelligence Systems

Course code: EEM  600:    Course title:  Principles of Artificial Intelligence

My Research Focus:
Pattern Recognition and Processing
Machine Vision

EEG Classifications and Decoding

Computational Intelligence

Control, How can we build artificial intelligence that understands human acts?
Translation between different languages, Natural language inference

Course credits: 4,    Pre-requisites:  None


Course Textbook:

A: Primary Texts:

[1] Rudolf Kruse et al.,  Computational Intelligence: A Methodological Introduction, 2nd Edition,  Springer, New York, 2016.  ISBN 978-1-4471-7294-9
Bookstore or online, e.g., Springer
[2] David Poole and Alan Mackworth "Artificial Intelligence: Foundations of Computational Agents".

Cambridge University Press, (1st edition: 2010, 2nd edition: 2017). (available online. The section references below are to the 2nd edition.)

B: Other Texts:

[3] Stuart Russell and Peter Norvig Artificial Intelligence: A Modern Approach  Pearson Series in Artificial Intelligence, 2020, Fourth Edition,

[4] C: J-S. R. Jang, C-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997,

Other resources used (e.g. e-Learning, field visits, periodicals, software, etc.).



A standard undergraduate-level background in Maths, Computational Skills, and Design. 

The Course will be fully supported by a large number of laboratory computational codes, and practical works.  

Hence,  a student will learn the basics of  matlab, C++, ....  python, and use it as a support for analysis and design of lab oriented experiments.  

coding prereq.:  

AI Algorithms,  Genetics, Neural Net,  Foraging, Fuzzy-Neural, Learning,  Evolution.


Course Description

(from the UOB Catalog):

Historical background and foundations of artificial intelligence. Major Development of AI; the Philosophical Background. Introduction to concepts of Intelligent agents and their use for Engineering applications.  The search algorithms and concepts (A* Search and Iterative Deepening Methods). Classes of AI and Concepts of computational AI. Artificial Intelligence verses Machine learning and Deep Learning.  AI as Logical formalisms, propositional and first order predicate calculus Planning, from STRIPS to other Partial Order Planning Probability and uncertainty, the Bayesian inference and Bayes computational networks. Machine learning. AI based decision trees. Classes of ANN Neural Nets.  The hill climbing, and genetic programming (algorithms). Other classes of Engineering AI, Vision systems, IoT, Bigdata, Robotics, and Computational Systems. AI and Ethics:  The Ethical Principles of AI. AI Management, principles and fundamentals. Through various examples, students will learn how to apply intelligent control techniques to real engineering problems with Matlab.

Teaching Structure:
The course is consisting of two (2-Hours) in-class sessions per week, making it (4-Hours) a week.
The course content is delivered in a lecture format, with four assignments, a midterm, and a final exam (A Project Work).

Homework Assignments (60%)
Up to about 3-5% for optional Extra Credit Projects

Homework and Assignments (20%):  There is roughly one homework assignment per 3-weeks, aside from weeks with exams.
Midterm      (40%)

Final Exam  (40%)



Complete  Class Lectures, and Notes:        Lectures Notes: Access via UoB Blackboard link;  UoB BB course contenet

EEM600, Course Syllabus Sheet:                EEM600 -QAAC Form

Samples of Midterms, and Finals:              SAMPLES OF MIDTERMS, FINALS, TUTORIALS

Lectures Notes: Access via UoB Blackboard link:


Object Oriented Programming using Matlab (OOP),

uses of classes (class), objects (obj) and data structure (struct) .. if you would like to use this approach in programming for this course, this will be great. 

This is optional, but it is always good to learn latest advanced programming tools. 

Download slides about Matlab from the Advanced MATLAB for Scientific Computing, Stanford University.   OOP-Matlab Press here to Download

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