University of North Carolina at Charlotte · Courses
SEGR
36 courses with the subject SEGR, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
SEGR 2105Computational Methods for Systems Engineering I3
Prerequisite(s): ENGR 1300, ENGR 1302, and MATH 1242 with grades of C or above or permission of department; Systems Engineering major; and Sophomore, Junior, or Senior standing. Introduces programming languages and computational algorithms that are often used by Systems Engineers. Object-Oriented Programming Language, specifically Python, is emphasized.
Prerequisite(s): ENGR 1300 with a grade of C or better; and Engineering major or minor. Focuses on the fundamentals of engineering management, providing students with management principles and practices and the role of engineering management professionals. Technology advances and their impact on management philosophies, including globalization and artificial intelligence will be discussed.
SEGR 2121Introduction to Logistics Systems and Supply Chains3
Prerequisite(s): ENGR 1300 with a grade of C or better, and Engineering major or minor. Focuses on the fundamentals in logistics systems and supply chain operations. It provides students the understanding of the operations in logistics systems and global supply chains and the roles of logistics/supply chain professionals in global business environment. In addition, the term project assignment requires to embrace the applications of AI in the supply chain operations.
SEGR 3102System Simulation, Modeling, and Analysis3
Prerequisite(s): STAT 3128 with grade of C or above; and Engineering major or minor. Focuses on the study of discrete-event simulation and its integration with machine learning techniques for the analysis, design, and optimization of complex systems. Students will learn how to use simulation software for simulation modeling and analysis, and apply machine learning algorithms specifically reinforcement learning, to: (i) Model and analyze complex systems, (ii) Optimize system performance, (iii) Make data-driven decisions, and (iv) Improve system design and operations. SEGR 3103. Human System Interface. (3) Prerequisite(s): SEGR 2105 with grade of C or above or permission of department; and Engineering major or minor. Explores the interface between human, organizational, and systems operations, focusing on the impact of human and cultural Course Descriptions | 805
SEGR 3105Computational Methods for Systems Engineering II3
Prerequisite(s): SEGR 2105 with grade of C or above; and Engineering major or minor. Topics in data analytics and basic machine learning skills, such as regression, classification, data processing, and model validation, by using R programming and packages.
SEGR 3132Facilities Planning and Material Handling Systems3
Prerequisite(s): SEGR 2101 with grade of C or above or permission of department; and Engineering major or minor. Focuses on the basics in facility planning, plant layout design, material handling systems design and integration, and warehousing. The emphasis is on the effective design and integration of plant layout, material handling systems, and warehousing for supply chain operations.
Unrestricted Elective Courses, Double Major and/or Minor to Complete Requirements for Graduation Students must earn a minimum of 120 credit hours to graduate. This requirement can be fulfilled through a combination of elective courses, a minor, or a double major. The 120-credit minimum must be satisfied regardless of the specific academic path chosen (e.g., a minor combined with electives). Degree Total = 120 Credit Hours
(1) Prerequisite(s): ENGR 3500; and Engineering major or minor. Required of students during semesters immediately following each work assignment for presentation of engineering reports on co-op work done in the prior semester. Graded on a Pass/No Credit Basis. May be repeated for credit.
SEGR 3890Individualized Study. (1 to 3) Prerequisite(s): Permission
of department. Supervised individual study within an area of a student’s particular interest which is beyond the scope of existing courses. May be repeated for credit up to 3 credit hours.
SEGR 4101Network Modeling and Analysis. (3) Prerequisite(s): SEGR
3201 with grade of C or above or SEGR 4952 with grade of C or above; and Engineering major or minor. Explores formulation and solution of optimization problems using network flow algorithms. Topics include: minimum flow problems shortest path, maximum flow, transportation, assignment, minimum spanning trees. Efficient solution algorithms are investigated.
SEGR 4142Reliability Management and Survival Analysis. (3) Cross
listed Course(s): EMGT 5142. Prerequisite(s): STAT 3128 with grade of C or above; and Engineering major or minor. Introduces various reliability and survival analysis techniques. Topics include: reliability/survival functions, failure/hazard rate functions; parametric/non- parametric/semi-parametric techniques; Jensen Shannon Divergence, Kullback-Leibler Divergence, and Wasserstein distance for Generative Data Modeling; Conditional Value at Risk.
SEGR 4150Leadership Skills for Engineers. (3) Prerequisite(s): Junior
or Senior standing and Engineering major or minor. Focuses on skills needed to be an effective leader in business and industry in the 21st Century. The course includes introduction to leadership styles and how they are employed in organizations. The course covers leadership skills and competencies and introduces students to the impact of AI and global communications on organization and leadership.
SEGR 4154Bayesian Analysis for Human Decision. (3) Cross-listed
Course(s): EMGT 5154. Prerequisite(s): STAT 3128 with grade of C or above. The Bayesian approach to decision-making with numerous applications in engineering, business, and healthcare. Topics include Information Theory; Signal Detection and ROC curve; Principle Components and Structural Equation Modeling; d-Separation, Bayesian networks and Causality Inference. May be repeated for credit.
SEGR 4201Fundamentals of Deterministic System Analysis3
Cross-listed Course(s): EMGT 5201. Prerequisite(s): MATH 2164. The course is partitioned into three modules: refresher of linear algebra with introduction to data analytics applications, continuous optimization focused on linear systems, and discrete optimization by integer programming and dynamic programming. May be repeated for credit.
Unrestricted Elective Courses, Double Major and/or Minor to Complete Requirements for Graduation Students must earn a minimum of 120 credit hours to graduate. This requirement can be fulfilled through a combination of elective courses, a minor, or a double major. The 120-credit minimum must be satisfied regardless of the specific academic path chosen (e.g., a minor combined with electives). Degree Total = 120 Credit Hours
