{"id":45,"title":"Artificial Intelligence","credit_hour":"3","lecture_hour":"45","outcome":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ul>\r\n<li>Apply artificial intelligence techniques, including search heuristics, knowledge representation, planning and reasoning<\/li>\r\n<li>Describe the key components of the artificial intelligence (AI) field<\/li>\r\n<li>Explain search strategies<\/li>\r\n<li>Solve problems by applying a suitable search method<\/li>\r\n<li>Analyze and apply knowledge representation<\/li>\r\n<li>Describe and list the key aspects of planning in artificial intelligence<\/li>\r\n<li>Analyze and apply probability theorem and Bayesian networks<\/li>\r\n<li>Describe the key aspects of intelligent agents<\/li>\r\n<\/ul>\r\n<\/body>\r\n<\/html>","description":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<p style=\"text-align: justify;\">Artificial Intelligence (AI) is the study of making optimal decisions given incomplete information and limited resources. This unit covers the foundational concepts and programming techniques of AI: search and problem solving methods, knowledge representation, reasoning, intelligent agents and natural language processing. Additional aspects of AI discussed include logic, uncertainty, puzzle solvers, simulative and cognitive process, expert systems and data processing.<\/p>\r\n<\/body>\r\n<\/html>","books":"<!DOCTYPE html>\r\n<html>\r\n<head>\r\n<\/head>\r\n<body>\r\n<ol>\r\n<li><a href=\"https:\/\/www.amazon.com\/Artificial-Intelligence-Modern-Approach-3rd\/dp\/0136042597\" target=\"_blank\"><em>Artificial Intelligence: A Modern Approach (3rd Edition<\/em>) by Stuart Russell and Peter Norvig<\/a><\/li>\r\n<li><a href=\"https:\/\/www.amazon.com\/Elements-Statistical-Learning-Prediction-Statistics\/dp\/0387848576\" target=\"_blank\"><em>The Elements of Statistical Learning<\/em> by Hastie, Tibshirani, and Friedman<\/a><\/li>\r\n<\/ol>\r\n<\/body>\r\n<\/html>","created_at":"2016-09-03 13:11:25","updated_at":"2017-01-25 11:56:58"} Details | Department of Computer Science and Engineering, IUB

CEN 425: Artificial Intelligence

Offered Under: B.Sc. in Computer Engineering (CEN)

Description

Artificial Intelligence (AI) is the study of making optimal decisions given incomplete information and limited resources. This unit covers the foundational concepts and programming techniques of AI: search and problem solving methods, knowledge representation, reasoning, intelligent agents and natural language processing. Additional aspects of AI discussed include logic, uncertainty, puzzle solvers, simulative and cognitive process, expert systems and data processing.

Prerequisites:

CEN 317 + Lab : Numerical Methods

Course Type	Major
Credit Hour	3
Lecture Hour	45

Expected Outcome(s):

Apply artificial intelligence techniques, including search heuristics, knowledge representation, planning and reasoning
Describe the key components of the artificial intelligence (AI) field
Explain search strategies
Solve problems by applying a suitable search method
Analyze and apply knowledge representation
Describe and list the key aspects of planning in artificial intelligence
Analyze and apply probability theorem and Bayesian networks
Describe the key aspects of intelligent agents

Suggested Books:

Grading Policy:

Biweekly Quiz, One Midterm Exam, One Final Exam, Project

Letter Grade	Marks	Grade Point
A	90 - 100	4.00
A-	85 - 89	3.70
B+	80 - 84	3.30
B	75 - 79	3.00
B-	70 - 74	2.70
C+	65 - 69	2.30
C	60 - 64	2.00
C-	55 - 59	1.70
D+	50 - 54	1.30
D	45 - 49	1.00
F	00 - 44	0.00