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| CS 57100 - Artificial Intelligence | ||||||||||||||||||
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Credit Hours: 3.00. Artificial Intelligence (AI) systems are increasingly being deployed in many real-world tasks. This course provides an introduction to the fundamental principles and applications of AI. The course covers classic material including search-based methods, probabilistic reasoning, game playing, decision making, exact and approximate inference, causal learning, and reinforcement learning as well as selected advanced topics. The focus of the course is on foundational methods and current techniques for building AI systems that exhibit 'intelligent' behavior and can 'learn' from experience. The course assumes students are familiar with basic concepts in analysis, linear algebra, optimization, discrete mathematics, elementary probability, statistics, data structures, and algorithms. Students are expected to have good programming and software development skills and have a working knowledge of Python and Java.
3.000 Credit hours Syllabus Available Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture Offered By: College of Science Department: Computer Science Course Attributes: Upper Division May be offered at any of the following campuses: West Lafayette Learning Outcomes: 1. Assess and explain the applicability, strengths, and weaknesses of the basic knowledge representation, problem-solving, and learning methods in solving a particular problem. (E,W) 2. Predict the behavior and estimate the cost (in time and space) of different heuristic and optimal search methods, and choose the appropriate method for particular problems. (W,P) 3. Develop small logic-based, rule-based, and search-based systems; be able to predict performance characteristics. (P) 4. Predict the behavior of basic machine-learning methods, and choose the appropriate method for particular problems. (W,P) 5. Communicate critical key issues in AI-related to knowledge representation, problem-solving, and learning for a specific problem. (W) 6. Propose, evaluate, and implement effective solutions to problems requiring AI techniques. (P) 7. Articulate key problems, both technical and philosophical, in the development of artificial intelligence systems. (E,W) Restrictions: Must be enrolled in one of the following Programs: Computer Science-PHD Computer Science-MS Computer Science-MS Prerequisites: GR CS 57100 Requisites General Requirements: ( Student Attribute: GR May not be taken concurrently. ) or ( Course or Test: CS 38100 Minimum Grade of C May not be taken concurrently. and Rule: 1: STAT35000orSTAT35500 for a total of 1 conditions1 course ) STAT 35000 Minimum Grade of C May not be taken concurrently. STAT 35500 Minimum Grade of C May not be taken concurrently. End of rule 1 and Rule: 2: MA26500orMA35100 for a total of 1 conditions1 course MA 26500 Minimum Grade of C May not be taken concurrently. MA 35100 Minimum Grade of C May not be taken concurrently. End of rule 2 Short Title: Artificial Intelligence Course Configurations:
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