Course
| code | CS468 |
| credit_hours | 3 |
| title | Advanced Artificial Intelligence |
| arbic title | |
| prequisites | CS366 |
| credit hours | 3 |
| Description/Outcomes | This course allows the introduction of material relating to Current advances in artificial intelligence topics, and technology. The course will focus on artificial neural networks, expert systems and machine learning, which are essential components of computational and statistical methods, and theoretical computer science. The course will also discuss recent applications of machine learning, such as data mining, face and speech recognition, and text and web data processing |
| arabic Description/Outcomes | |
| objectives | 1. Expert Systems
2. Machine Learning: Classification, Ensemble Methods, Clustering, Decision Tree, and Association Rules.
3. Intelligent Mobile Agents
4. Natural Language Processing
5. AI Applications: image and speech recognition, data mining, and web mining, and
6. Implementing software applications, Design intelligent systems that can adapt to both uncertainties and changes in their environments.
7. Understand AI as the design of agents. |
| arabic objectives | |
| ref. books | 1- Tom Mitchell, Machine Learning, McGraw-Hill.
2- Nils J. Nilsson, Artificial Intelligence: A New Synthesis, Morgan Kaufmann.
3- George F. Luger, Artificial Intelligence, 6th edition, Addison-Wesley.
4- Michael Negnevitsky, Artificial Intelligence, 2nd edition, Addison-Wesley. |
| arabic ref. books | |
| textbook | Russell S. and Norvig P., Artificial Intelligence: A modern Approach, Prentice-Hall, 3rd Edition. |
| arabic textbook | |
| objective set | |
| content set | |
| course file |
530_CS468_CS468.pdf |