University :Mansoura University |
Faculty :Faculty of Computers and Information |
Department :Computer Science |
|
| 1- Course data :- |
| | Code: | عح372 | | Course title: | Artificial Intelligence | | Year/Level: | ثالثة نظم المعلومات | | Program Title: | | | Specialization: | | | Teaching Hours: | Theoretical: | 3 | Tutorial: | | Practical: | 3 |
|
| 2- Course aims :- |
| - Cover the basic ideas of Artificial Intelligence, AI terminology, concepts, and goals.
- Formulate and assess problems in artificial intelligence.
- Assess the strengths and weaknesses of several methods for representing knowledge.
- Assess the strengths and weaknesses of several AI algorithms in areas such as bland search, heuristic search, game search, logical inference, statistical inference, decision theory, planning, machine learning, neural networks, and natural language processing.
- Understand, identify, and evaluate AI techniques.
- Implement software solutions to a wide-variety of problems generally considered to require artificial intelligence.
- Examine knowledge representation, constraint exploitation, symbolic reasoning, and explanation generation.
- Study programming techniques used for finding alternatives, planning sequences of operations, and playing games.
- Understand the role of artificial intelligence (AI) in the greater context of computer science.
- Write programs in an AI-based language, specially PROLOG.
- Identify and apply AI methods to real-world applications.
|
| 3- Course Learning Outcomes :- |
| |
| 4- Course contents :- |
| | No | Topics | Week |
|---|
| 1 | Constraint Satisfaction | | | 2 | Knowledge Representation | | | 3 | Reasoning | | | 4 | Planning | | | 5 | Uncertainly | | | 6 | Introduction | | | 7 | Search Problems | | | 8 | Blind Search Strategies | | | 9 | Heuristic Search Strategies | |
|
|
| 5- Teaching and learning methods :- |
| | S | Method |
|---|
| Computer + Data Show + power point slides | | Blackboard | | Free Discussion | | Different Software |
|
|
| 6- Teaching and learning methods of disables :- |
| No data found. |
|
| 7- Student assessment :- |
| A. Timing |
| | No | Method | Week |
|---|
| 1 | Mid-Term exam, Reports and Homework | 14 | | 2 | Oral and Project | 15 |
|
| B. Degree |
| | No | Method | Degree |
|---|
| 1 | Mid_term examination | 5 | | 2 | Final_term examination | 75 | | 3 | Oral examination | 5 | | 4 | Practical examination | 10 | | 5 | Semester work | | | 6 | Other types of asessment | 5 | | Total | 100% |
|
|
| 8- List of books and references |
| | S | Item | Type |
|---|
| 1 | S. Russel and P. Norvig. Artificial Intelligence: A Modern Approach, 2nd Ed, 2003 | | | 2 | E. Rich and K. Knight. Artificial Intelligence, 2nd Ed, 1991. | | | 3 | Different Web Sites | | | 4 | Different Periodicals. | | | 5 | Some power point slits. | |
|
|
| 9- Matrix of knowledge and skills of the course |
| | S | Content | Study week |
|---|
| Constraint Satisfaction | | | Knowledge Representation | | | Reasoning | | | Planning | | | Uncertainly | | | Introduction | | | Search Problems | | | Blind Search Strategies | | | Heuristic Search Strategies | |
|
|
| Course Coordinator(s): - |
| - Tarek Tawfek Ahmed Hamza
|
| Head of department: - |
| |
