كلية الهندسة - جامعة عين شمس, الرئيسية

الرئيسية  >  كلية الهندسة - جامعة عين شمس, الرئيسية

Artificial Intelligence

What Will Learn?

  • Course Aims
    The aim of this course is to introduce the essential concepts in artificial that include a wide range of searching techniques and their application to real-world problems. Formulate problems using suitable knowledge representation. Use expert system to reason about knowledge. Understand the basic learning methods from real-world data.
  • Course Goals
  • Decent Work and Economic Growth
  • Industry, Innovation and Infrastructure
  • Sustainable Cities and Communities

Requirements

PHM311s AND CSE231s

Description

  • English Description

    Definition, symbolic versus computational artificial intelligence, applications. Intelligent agents. Knowledge representation and reasoning using logic, frames, scripts, semantic networks, case-based reasoning and production rules. Propositional logic: representation and logical inference. Expert systems: structure, inference engines and rule execution. Problem-solving as search, state space representation, uninformed search algorithms (e.g., depth first, breadth first), heuristics, informed search algorithms, optimal search, genetic algorithms, constraint satisfaction, adversarial search. Handling uncertainty: fuzzy logic and Bayesian networks. Introduction to machine learning: supervised learning, neural networks, expert systems with learning component.
  • Arabic Description

    Definition, symbolic versus computational artificial intelligence, applications. Intelligent agents. Knowledge representation and reasoning using logic, frames, scripts, semantic networks, case-based reasoning and production rules. Propositional logic: representation and logical inference. Expert systems: structure, inference engines and rule execution. Problem-solving as search, state space representation, uninformed search algorithms (e.g., depth first, breadth first), heuristics, informed search algorithms, optimal search, genetic algorithms, constraint satisfaction, adversarial search. Handling uncertainty: fuzzy logic and Bayesian networks. Introduction to machine learning: supervised learning, neural networks, expert systems with learning component.
  • قسم
    هندسة الحاسبات والنظم
  • الساعات المعتمدة
    3
  • الدرجات
    الإجمالي ( 100 ) = نصف العام (20) + tr.Student Activities (20 = tr.Industry 0% , tr.Project 5% , tr.Self_learning 0% , tr.Seminar 15% ) + tr.Oral/Practical (10) + درجة الامتحان (50)
  • الساعات
    ساعات المحاضرة: 3, ساعات التعليم: 1, ساعات المعمل: 0
  • Required SWL
    100
  • Equivalent ECTS
    4
  • - Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. 4th Edition, Pearson Education, Inc., 2020,
  • - Patrick Henry Winston, Artificial Intelligence, 3rd Edition, Addison Wesley, 1993 - Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach. 4th Edition, Pearson Education, Inc., 2020,.