PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
ENM 543	ARTIFICIAL INTELLIGENCE METHODOLOGIES IN INDUSTRIAL ENGINEERING	3 + 0	2nd Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	The course aims to equip industrial engineering master’s students with a deep understanding of various artificial intelligence methodologies and their applications in optimizing and enhancing industrial systems. The focus will be on practical and theoretical aspects of AI techniques such as machine learning, heuristic algorithms, and data analytics, specifically tailored to address challenges in production, logistics, and sustainability within industrial settings.
Course Content	Introduction to AI and its relevance to industrial engineering. Overview of machine learning algorithms and their applications. Heuristic and metaheuristic optimization techniques. Application of AI in production planning and control. AI-driven solutions for logistics and supply chain management. Use of AI for sustainability and environmental impact assessments. Case studies and real-world applications of AI in industrial engineering. Future trends and ethical considerations in AI applications.
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.

COURSE LEARNING OUTCOMES

1	İlk kazanım otomatik olarak atılmaktadır. Güncellemeniz gerekmektedir. Yeni Eklemek için (+) YENİ KAZANIM EKLE tıklayınız.

COURSE'S CONTRIBUTION TO PROGRAM

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Assignments	4	5	20
Mid-terms	1	60	60
Final examination	1	73	73
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

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