Database Systems
CSE 5290 Artificial Intelligence
Fall 2020
2018–2020 Catalog Data: CSE 5290 Artificial Intelligence (3 credits). Introduces the theoretical foundations of artificial intelligence, focusing on the areas of automated reasoning, search and heuristics. Introduces an AI language to implement concepts.
Background knowledge equivalent to CSE 2010 Algorithms and Data Structures. Elective
Prerequisites by Topic: Data structures, algorithm types, graph algorithms, recursion, and complexity analyses.
Textbook (T) and References (R):
S. Russell and P. Norvig, Artificial Intelligence: Modern Approach. Pearson, third ed.,
2010. (T)
Course Outcomes & Related Student Outcomes: The students will be able to
• Describe concepts and topics in artificial intelligence.
• Use problem-solving heuristics and search in the analysis of artificial intelligence problems and algorithms.
• Design of basic AI algorithms in constraints processing, planning, logical reasoning, uncertainty reasoning or machine learning.
• Develop some data analytics skill.
• Improve team skills via group projects.
Topics Covered and Associated Time:
• Problem Solving by Search: 5/26 lectures: 19%
• Reasoning and Logic: 5/26: 19%
• Uncertainty in knowledge: 5/26: 19%
• Machine learning and Data Analytics: 5/26: 19%
• Student presentations, demo, tests and discussions: 6/26: 24%
Schedule:
Offered in every Semester
Class/Lab/Recitation Schedule: Two 70-minutes lectures per week
Prepared by: Debasis Mitra, Ph.D., Professor (July 30, 2020)
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This course may be recorded for use by students or faculty. Enrolled students are subject to having their images and voices recorded during the classroom presentations, remote access learning, and online course discussions. Course participants should have no expectation of privacy regarding their participation in the class. Recordings may not be reproduced, shared with those not registered in the course, or uploaded to other online environments. All recordings will be deleted at the conclusion of the academic term.
In accordance with “Florida Tech Safe: Return to Learn” procedures, instructors will enforce Florida Tech’s mandatory face covering policy in all classrooms and teaching labs. All students MUST wear appropriate face coverings that cover their mouth and nose during all face-to-face course meetings. Students who fail to comply with this policy WILL BE REQUIRED to leave the classroom immediately. Students unable to comply may contact the Dean of Students Rodney Bowers for further options.
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