Introduction to Artificial Intelligence

  • College Of Computing & Information Technology |
  • English

Description

Introduction to basic methods of Artificial Intelligence (AI) such as problem solving, searching techniques, machine learning and knowledge representation. Through discussions, small projects, and examples, students learn what AI is, some of the major developments in the field, promising directions, and the techniques for making computers exhibit intelligent behavior. Students make use of available tools and explore some areas of applications.

Program

Software Engineering bachelor`s degree Program

Objectives

  • - Understand the basic concepts of artificial intelligence.
    - Understand state space representation.
    - Compare different problem-solving strategies based on algorithms and heuristics.
    - Understand the basic concepts of Genetic Algorithm.
    - Understand the basic concepts of machine learning using artificial neural networks.
    - Understand different Methods for knowledge representations.

Textbook

Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Pearson.

Course Content

content serial Description
1Introduction to AI Definition, History and Goals.
2Intelligent Agents and Problem Solving.
3State Space Representation and Search Techniques (Blind search) .
4Search Techniques (Heuristic Search,..).
5A* Algorithm, Admissibility, Monotonicity and Informedness of a heuristic function.
6Game trees and Alpha Beta Pruning Algorithm.
7Propositional Logic
8First Order Logic
9Introduction to Machine Learning - Supervised Learning.
10Supervised Learning cont.
11Perceptron Learning Algorithm.
12Artificial Neural Networks.
13Unsupervised Learning (K-means).
14New trends in Artificial Intelligence.
15Course Review and Conclusion.
1Introduction to AI Definition, History and Goals.
2Intelligent Agents and Problem Solving.
3State Space Representation and Search Techniques (Blind search) .
4Search Techniques (Heuristic Search,..).
5A* Algorithm, Admissibility, Monotonicity and Informedness of a heuristic function.
6Game trees and Alpha Beta Pruning Algorithm.
7Propositional Logic
8First Order Logic
9Introduction to Machine Learning - Supervised Learning.
10Supervised Learning cont.
11Perceptron Learning Algorithm.
12Artificial Neural Networks.
13Unsupervised Learning (K-means).
14New trends in Artificial Intelligence.
15Course Review and Conclusion.

Markets and Career

  • Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
  • Electrical power feeding for civil and military marine and aviation utilities.
  • Electrical works in construction engineering.
Courses
  • Degree Bachelor
  • Code: CCS3601
  • Credit hrs: 3
  • Prequisites: CCS1001 , CCS2401
Download.pdf
Apply Now

Start your application

Start The your journey to your new career.
SUBMIT IT NOW