Undergraduate Courses

ISE Courses

All undergraduate students need to complete three technical electives in addition to the required core courses of their program. Options for technical electives can be found here. Students should refer to the major requirements and guidesheet for their term of entry to the program to ensure they are on-track for completion. Progress will be reviewed at least once per semester with an academic advisor within the department.

• ISE 211 - Engineering Economics

  The fundamentals of engineering economy are introduced in this course. Topics covered include time value of money, equivalence, cash flows all at varying interest rates and points of time. The factors commonly used in industry for economic evaluation of alternatives are introduced and applied in this course. The analysis includes both a before tax and after tax evaluation of competing investment alternatives. Prerequisites: Math 227 and EDD 112 or permission of instructor. Offered in the Spring semester. 4 credits. Levels: Undergraduate

• ISE 212 - Engineering Computing

  The objectives of the course are to: demonstrate the ability to design systems for automating processes in manufacturing, demonstrate problem-solving skills in automation, and to demonstrate the skill of using the LabVIEW and MATLAB software packages. Prerequisite: EDD 112 or permission of instructor. Offered in the Spring semester. 4 credits. Levels: Undergraduate

• ISE 231 - Human Factors

  Review of the concepts involved in the application of scientific principles, methods, and history to the development of engineering systems in which people play a significant role. Primary focus is on the man/machine interface and how to design for the human being as part of an overall system. Prerequisite: MATH 226/227 or permission of instructor. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 261 - Probabilistic Systems I

  This course provides an introduction to probability models and statistical methods most likely to be encountered and used by students in their careers in engineering and the natural sciences. This introduction will emphasize, from the outset, that variation is the source from which all statistical methodology flows. Discussion includes the practical aspects of data collection and descriptive statistics with an introduction to the basic concepts of probability theory and probability distributions, correlation, point estimation, confidence intervals, and test of hypothesis. Prerequisites: Math 227 and EDD 112 or permission of instructor. Offered in the Spring semester. 4 credits. Levels: Undergraduate

• ISE 295 - Seminar Course

  Development of the non-technical skills essential to effective engineering. Focus is on the overview of ISE curriculum and review of technical elective options. Review of internships, resume building, issues relevant to careers in ISE (e.g., typical tasks done by ISEs) are explored. Discussion and exploration of opportunities within program. Prerequisites: Sophomore Standing. Offered in the Fall semester. 1 credit. Levels: Undergraduate

• ISE 311 - Enterprise Systems

  Course introduces the concepts, design and planning of operating systems, with particular emphasis on manufacturing systems. Topics include introduction to lean manufacturing, JIT, Kanban, value stream mapping, standard times, MRP, inventory control, etc. The course includes plant tours to local industries that practice the concepts of the Toyota production system. Prerequisite: ISE 211 or permission of instructor. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 312 - Manufacturing Systems

  This course has three main areas of focus: production and inventory control, planning and design of manufacturing facilities, and understanding the physical fundamentals of processes and is designed mainly for engineering students intent on following an engineering career in a manufacturing industry. This course covers the models, networking, and systems needed to design and manage a manufacturing enterprise. Topics include facility design and material handling, forecasting techniques, demand management, economic lot size, inventory management, and scheduling methods. This is considered a technical elective. Prerequisite: ISE 311 or consent of department chair. Prerequisite: Junior standing in the Watson School or permission of instructor. Offered in the Spring semester. 3 credits. Levels: Undergraduate

• ISE 314 - Computer Program for Engineers

  This course provides an introduction to computer programming and its applications for industrial and systems engineering (ISE) students emphasizing modern software engineering techniques in the context of industrial systems. Topics will include the fundamental concepts and applications of computer programming, software engineering, database management, computational problem solving, and statistical techniques for data mining. In this course, programming languages such as Python, VB.Net, or Matlab will be taught along with Excel VBA and SQL. Students will learn how to apply computer-programming techniques to solve different ISE problems. Prerequisite: ISE 261 or permission of instructor. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 315 - Enterprise Resource Planning

  This course introduces the student to the main areas of production, including production planning, control, master scheduling, finance and human resources. It provides a hands on approach to these areas through an Enterprise Resource planning software. Prerequisites: Junior standing in ISE or consent of instructor. Term offered varies. 3 credits Levels: Undergraduate

• ISE 320 - Optimiz & Operation Research I

  Operations research (OR) is devoted to determination of the optimal course of action of a decision problem given resource restrictions. This course primarily covers deterministic optimization and operations research techniques. Following a review of linear algebra, students learn how to mathematically model an engineering problem, how to solve the problem to optimality and how to perform sensitivity analyses on the results. Students learn linear programming (LP), integer programming (IP), branch-and-bound (B & B), and other optimization techniques. Special emphasis on the solution of engineering decision making includes the following areas: transportation models; network models; inventory models; assignment problems; decision making under risk and uncertainty; and game theory. For non-ISE students using this course as an elective for the Sustainability Engineering minor, application of these techniques as applied to decision-making for sustainability are included. Prerequisite: Math 304 or permission of instructor. Offered in the Spring semester. 4 credits. Levels: Undergraduate

• ISE 362 - Probabilistic Systems II & DOE

  Methods of inference involving two independent samples and paired data are presented. The analysis of variance is examined for single-factor and multi-factor experiments. Regression analysis for simple linear models and correlation are discussed followed by non-linear and multiple regression models. A practical, yet fundamental, approach for building quality control charts from statistical concepts, as well as a goodness-of-fit test for testing discrete and continuous underlying distributions, are reviewed. Prerequisites: ISE 261 Probabilistic Systems I or permission of instructor. Offered in the Fall semester. 4 credits Levels: Undergraduate

• ISE 363 - Quality Engineering

  This course is designed to introduce the student to techniques required to maintain and improve quality within manufacturing organizations and the service sector through the use of statistical methodologies. The course covers concepts of quality, quality management and assurance, product quality, design of quality, six sigma, lean (using quality to eliminate waste), control charting, statistical process control, and quality improvement through design by considering concept development and implementation. Traditional and modern quality systems will be discussed including the work of such quality gurus like Taguchi, Deming, Juran, and Shewhart. Prerequisites: ISE 362 or permission of instructor. Offered in the Spring semester. 4 credits. Levels: Undergraduate

• ISE 364 - Eng Project Management

  Effective Engineering Project Management is critical to business and organizational success. Through in-class practice of concepts and processes, learn proven techniques, enhanced skills and best practice principles to lay a solid Engineering Project Management foundation. Through the discipline of initiating, planning, executing, controlling, and closing a project, you will grasp a thorough understanding of how to make your engineering projects successful. Microsoft Project software will be used to demonstrate activities, duration, task relationships, Gantt Charts, network diagrams and the critical path method with a case study of contemporary engineering project. Prerequisites: ISE 211 or permission of instructor. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 411 - Production & Schedule Control

  This course covers general concepts of production planning and control but goes more into detail of the concepts and mathematics of scheduling applications and theory. Upon completion of the course, the student will be able to apply mathematical techniques in developing solutions to “production scheduling” problems. The “production scheduling” terminology may seem like these techniques are applicable only to manufacturing, however, they have broad applications across many industries and sectors including, but not limited, to healthcare, service industries, food processing, etc. Prerequisites: ISE 311 and senior-level standing, or permission of the instructor. Offered for the Fall semester. 3 credits. Levels: Undergraduate

• ISE 415 - Operations Mgmt Supply Chains

  Course deals with management of supply chains, in particular, with the operational aspects. A broad overview of supply chains of a company is introduced, together with performance measures and needed critical success factors. The course concentrates on supplies, inventories, manufacturing, and logistics of distribution. Managerial aspects as well as mathematical modeling for better planning and control will be covered. This course is considered a technical elective for undergraduate students. Prerequisite: ISE 311 and ISE 320 or consent of department chair. Crosslisted with SSIE 515. Prerequisite: Senior standing in ISE or consent of instructor. Offered in the spring semester. 3 credits. Levels: Undergraduate

• ISE 416X - Fund. of Energy Sys. Analytics

  This course provides fundamental knowledge of the application of Industrial and Systems Engineering in the Energy field. It focuses on the modeling, design, simulation, and optimization of alternative and conventional energy technologies, the societal and environmental impact of technology developments, and the economic benefits of those developments. Recent literature that covers a wide range of ISE topics related to energy systems such as transportation energy, building energy, manufacturing energy, solar energy, wind energy, bioenergy, greenhouse gas emission, and smart grid operations will be discussed in this course. Students will gain breadth and depth of knowledge, and an interdisciplinary understanding of the contemporary need for energy solutions. 3 Credits. Prerequisites: Senior level standing. Offered in fall or spring. Levels: Undergraduate

• ISE 418 - Collective Dyn of Complex Syst

  Introduces students to the study of collective dynamics demonstrated by various natural, social and artificial complex systems, i.e., systems made of a massive amount of lower-level components interacting with each other in a nonlinear way. Discusses several computational modeling frameworks, including agent-based models (particle models, ecological and evolutionary models, game-theoretic models), complex network models (small-world and scale-free networks, dynamical networks, adaptive networks), and spatial models (cellular automata, partial differential equations). Also discusses mathematical concepts and tools to analyze and understand their behavior, e.g., mean-field approximation, linear stability analysis, scaling, renormalization, bifurcation, chaos, pattern formation, and phase transition. Python will be used as a primary computer programming language for modeling and simulation. Prior computer programming experience is helpful, but not strictly required. Prerequisite: ISE 314 or permission of instructor. Cross listed with SSIE 523. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 419 - Applied Soft Computing

  Covers relatively new approaches to machine intelligence known collectively as "soft computing". Introduces various types of fuzzy inference systems, neural networks, and genetic algorithms, along with several synergistic approaches for combining them as hybrid intelligent systems. Emphasis is on applications, including modeling, prediction, design, control, databases and data mining. This course is considered a technical elective for undergraduate students. Prerequisites: Basic knowledge of calculus and discrete mathematics and competence in at least one programming language, or permission of instructor. Crosslisted with SSIE 519. Offered in the fall semester. 3 credits. Levels: Undergraduate

• ISE 420 - Optimiz & Operations Res II

  Operations research (OR) is devoted to the determination of the optimal course of action of a decision problem given resource restrictions. This course is intended as a second course in an Optimization and OR sequence and builds upon the material presented in ISE 320. ISE 320 primarily restricts attention to deterministic OR models. In addition to covering additional deterministic techniques (e.g., deterministic dynamic programming and additional inventory problems not covered in ISE 320, among others), ISE 420 covers probabilistic and advanced OR topics such as Monte Carlo simulation, fundamentals of queueing theory, probabilistic dynamic programming, and others. The course also introduces the student to emerging optimization techniques including, but not limited to, tabu search, simulated annealing, and genetic algorithms. Prerequisite: ISE 320 or permission of instructor. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 421 - Modeling And Simulation

  Model building, nature of simulation and material on the full range of simulation activities, such as input analysis, output analysis, verification and validation, and model animation. Includes random number generation; distribution functions and random variates; applications of discrete event simulation methods to queueing, inventory control and production planning problems; Markov processes, queueing theory and decision analysis. Prerequisites: ISE 362 and ISE 320 or permission of instructor. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 422 - Advanced Decision Modeling

  Course provides a broad foundation in decision models and techniques used in industry and research for technical and managerial problems. Topics include decision theory, risk and uncertainty, value of information, preference measurements, prioritization of alternatives, multiple objectives and hierarchical decisions. Prerequisite: ISE 362 or permission of the instructor. Cross-listed with SSIE 522. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 423 - Collective Dyn of Complex Syst

  Introduces students to the study of collective dynamics demonstrated by various natural, social and artificial complex systems, i.e., systems made of a massive amount of lower-level components interacting with each other in a nonlinear way. Discusses several computational modeling frameworks, including agent-based models (particle models, ecological and evolutionary models, game-theoretic models), complex network models (small-world and scale-free networks, dynamical networks, adaptive networks), and spatial models (cellular automata, partial differential equations). Also discusses mathematical concepts and tools to analyze and understand their behavior, e.g., mean-field approximation, linear stability analysis, scaling, renormalization, bifurcation, chaos, pattern formation, and phase transition. Python will be used as a primary computer programming language for modeling and simulation. Prior computer programming experience is helpful, but not strictly required. Prerequisite: ISE 314 or permission of instructor. Crosslisted with SSIE 523. Term offered varies. 3 credits. . Levels: Undergraduate

• ISE 426X - Sys Dynamics & Sys Thinking

  In this course, the basic concepts of systems thinking and system dynamics modeling will be introduced and students will understand, evaluate, and improve upon problems that manifest themselves in complex systems, such as diffusion of new technologies; global power consumption; fluctuating sales, production and earnings; environmental challenges such as urban development and poverty; healthcare and public health challenges such as disease spread. System dynamics is a simulation modeling process to quantify problems that unfold through time. In this iterative process, a problem that is pervasive throughout a system is defined, the structure of the system that generates the problem will be studied, and policies or practices that can change the system structure and behavior and therefore alleviate/solve the problem will be studied. Prerequisites: Senior level standing or permission of the instructor. Crosslisted with SSIE 526X. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 430 - Healthcare Policy Analysis

  This course provides an overview of issues and policies related to health care systems, with emphasis on health care systems within the United States. The course will apply various engineering tools and approaches for policy analysis and program planning in this area. Some potential future policy changes will also be discussed, as well as challenges with implementation and change management techniques. Cross-listed with SSIE 530. Prerequisites: Senior standing or permission of the instructor. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 434 - Fundamentals of Health Systems

  One of the growing systems in our society is that of the healthcare delivery system. The purpose of this course is to introduce the concepts behind the healthcare delivery systems and to focus upon the systems improvement or continuous improvement techniques available for complex systems. Topics would include improvement to, and problems with: organizational structure, managing change, the financial structure, the responsibility structure, quality data and implications of quality measures, use of clinical decision support systems and the caregiver's role in the system. There will also be a focus upon suppliers to the healthcare delivery system and the unique requirements placed upon their products and processes. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing or consent of department chair. Cross-listed with SSIE 534. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 437 - Ind & Sys Eng in Healthcare

  Introduction to health systems and healthcare delivery. The application of industrial and systems engineering principles to continuous process improvement in the healthcare domain will be studied. Concepts that will be addressed will include, but not be limited to, process mapping, optimization, scheduling, lean and flexible systems, quality enhancement, simulation, supply chain management, inventory control, and information management. The course is considered a technical elective for undergraduate students. Prerequisites: ISE 311 or permission of instructor. Crosslisted with SSIE 537. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 438 - Healthcare Financial Eng

  This course is intended to provide an overview of healthcare finance and the current financial environment for the healthcare industry and to learn how to apply engineering economics to healthcare financial management. It will provide information on financial and managerial accounting and how the use of Systems Science and Industrial and Systems Engineering principles can be applied to financial management concepts to allow for health-related organizations to make sound business decisions. Prerequisite: Senior standing or permission of instructor. Crosslisted with SSIE 538. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 439 - Human Factors Eng Healthcare

  This course introduces and emphasizes the role that human factors engineering/ergonomics plays in healthcare systems, with a focus on its applications to help improve quality, safety, efficiency, and effectiveness of patient care. Focused topics include human factors in workflow models; work system design for patient safety; human error analysis/taxonomies to reduce medical errors; task analysis and data collection methods in healthcare environments; clinical staff workload and patient safety; physical ergonomics in healthcare and human performance modeling; and diffusion and adoption of technology in healthcare, with emphasis on the usability and design of medical devices and information systems. Prerequisite: Senior standing or permission of instructor. Crosslisted with SSIE 539. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 440 - Intro to Systems Science

  Includes the following: a general characterization of systems science as a field of study; intellectual roots, philosophical assumptions and historical development of the field; an overview of fundamental systems concepts, principles and laws; and a survey of application areas of systems science and its implications for other fields of study. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing or permission of the department chair. Cross-listed with SSIE 501. Offered in the fall semester. 3 credits. Levels: Undergraduate

• ISE 448 - Healthcare Data Sci&Analytics

  Data analytics plays an increasingly greater role in healthcare organizations. However, many healthcare professionals lack training in this vital area. This course will cover advanced data analytics with applications in healthcare systems engineering. In specific, the course will cover the concepts and methods of the data analytics in three particular areas: (i) descriptive analytics, which includes data description and aggregation; (ii) predictive analytics, which uses machine learning and statistical modeling for prediction and forecasting; and (iii) prescriptive analytics, which makes use of the results of predictive analysis to optimize the decision making process. All introduced methods will be demonstrated along with a variety of data modalities collected from healthcare applications such as pervasive health, disease diagnosis, fraud detection, and pharmaceutical discovery along with medical decision support systems. Through the provided coursework, students will be able to learn a variety of methodologies on data processing and modeling and make the best use of healthcare data to facilitate medical decision making. Prerequisites: Senior level standing, ISE 314 or equivalent, or permission of the instructor. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 456 - Expert Systems In Manufacturin

  Computer-based decision-making tools in which a domain expert's knowledge is embedded are known as knowledge-based expert systems (KBESs). Expert systems allow such expert knowledge to be widely disseminated (e.g., throughout a company or throughout different facilities that a company has). This course introduces the student to all steps of development (e.g., knowledge representations, knowledge acquisition, and expert system development, among others) with special emphasis on manufacturing applications. The course will culminate with the students developing functioning prototype expert systems in a manufacturing area of their choice. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing in ISE or permission of instructor. Crosslisted with SSIE 556. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 462 - Cost Estimating For Engineers

  Changes in our society have resulted in major changes in manufacturing to the point at which labor costs are no longer the controlling cost, or even the major cost. Major costs have shifted to the material and material-related costs, with the overhead and burden costs almost as significant. While innovative design is critical to engineering, being profitable is also critical, and profit starts with determining the proper costs for a product or idea. Topics include costs of labor, equipment, material, overhead or burden, volume/cost relationships, use rates, collection, build-up of costs, costing of manufacturing operations, standard costs and variances. This course is considered a technical elective for undergraduate students. Prerequisite: ISE 211 or permission of instructor. Offered in the Spring semester. 3 credits. Levels: Undergraduate

• ISE 463 - Project Analysis And Control

  Course covers the topics of project planning, economic design making, costing and pricing. The topics include network planning, present worth, annual cost, rate of return, activity based costing, inflation, price change, etc. Prerequisite: ISE 211 or permission of instructor. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 464 - Elem Of Fuz Log & Fuz Set Thry

  Simple introduction to basic elements of fuzzy logic and fuzzy set theory, including an overview of classical logic and classical set theory. Included are basic concepts and properties of classical sets and fuzzy sets, classical relations and fuzzy relations, classical logic and fuzzy logic, and fuzzy arithmetic. The practical utility of fuzzy logic and fuzzy set theory is illustrated by describing selected applications in various areas of human affairs. This course is considered a technical elective for undergraduate students. Prerequisite: ISE 261 or permission of instructor. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 465 - Engineering Project Management

  Effective Engineering Project Management is critical to business and organizational success. Through in-class practice of concepts and processes, learn proven techniques, enhanced skills and best practice principles to lay a solid Engineering Project Management foundation. Through the discipline of initiating, planning, executing, controlling, and closing a project, you will grasp a thorough understanding of how to make your engineering projects successful. Microsoft Project software will be used to demonstrate activities, duration, task relationships, Gantt Charts, network diagrams and the critical path method with a case study of contemporary engineering project. Prerequisites: ISE 261 or permission of instructor. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 468X - Flexible & Hybrid Electronics

  Flexible and hybrid electronics integrate ultra-thin silicon semiconductor technology with non-traditional thin skin-like substrates establishing wearable devices for both human and machine. This course will cover design, materials, fabrication methods and evaluation of printed and thinned silicon-based electronics for applications such as smart energy, human health, and industrial sensing. Emphasis will be placed on fundamental understanding of the hard-soft materials interface, advances in materials printing, and approaches to make these systems robust for use. The course will promote understanding of the engineering requirements that lead to systems design for both manufacturing and reliability. 3 credits. Levels: Undergraduate

• ISE 469 - Materials for Manufacturing

  This course provides an overview of the materials used in manufacturing that are of significant economic, technical and industrial relevance. A special emphasis will be given to polymeric materials currently used in electronics manufacturing as well as those materials emerging for use in additive manufacturing and 3D printing. Selected materials will be classified by composition, properties, manufacturing methods, applications, economics and related supply chains. Prerequisites: Senior standing in engineering or science or permission of the instructor. Crosslisted with SSIE 569. Term offered varies. 3 credits. Levels: Undergraduate

• ISE 470 - Industrl Automation&Ctrl

  Industrial automation is a major field in the application of computer controls and the many advances in computer systems. The objectives of this course are to: demonstrate the ability to design systems for automating processes in manufacturing, demonstrate problem-solving skills in automation, and safely use the machines in the engineering laboratory to complete designed experiments. Lectures and laboratories include exploring the use of sensors, industrial robotics, numerical control, programmable logic controllers, machine vision, electrical circuits and the fundamentals of common electrical devices, fuzzy control, the implementation of online computer control, and the ability to use industrial technical software including Pro-Engineer and AutoCAD. Laboratory work and technical reports are required. Prerequisites: ISE 311 or consent of department chair. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 470X - International STEM Trip

  This course will explore Germany's approach to science, engineering, technology development and manufacturing. We will study, observe and discuss before, during and after organized travel: Germany and European history, the German culture and work ethic, the impact government organizations on economic development. We will learn why Germany is still considered a leader in manufacturing and the economic powerhouse of the European Union. We will answer: what can we learn from Germany and how will it influence our own contributions as scientists and engineers in the United States. Offered in the Summer term. 3 credits Levels: Undergraduate

• ISE 473 - Processes for Electr Mfg.

  The purpose is for the students to gain a broad knowledge and understanding of the basics of printed circuit board manufacturing and assembly. The course offers an introduction to surface mount and insertion mount components, materials and processes as well as to PCB design and manufacturing. Lectures will introduce assembly process flows and component types, PCB construction and defects solder paste printing and equipment, placement processes and equipment, reflow and ovens, flip chip assembly and underfilling, defects and mitigation, reliability optimization and testing. Efforts will be made to include visits to local industrial assembly facilities as well as equipment on campus. The overall goal is to provide the students with a basis for communicating and working with subject matter experts. This course is considered a technical elective for undergraduate students. Prerequisite: Senior standing or permission of instructor. Crosslisted with SSIE 578. Offered in the fall semester. 3 credits. Levels: Undergraduate

• ISE 483X - Evolutionary Sys & Bio-Inspire

  In this course, the fundamental concepts of bio-inspired computing are introduced with a focus on understanding how evolutionary systems are different from other complex systems in nature and society. Biological organisms cope with the demands of their environments using solutions quite unlike the traditional human-engineered approaches to problem solving. Biological systems tend to be adaptive, evolvable, resilient, reactive, and distributed. Bio-inspired computing is a field devoted to tackling complex problems using computational methods modeled after design principles encountered in nature. This course is strongly grounded on the foundations of complex systems science and theoretical biology. It aims to provide an understanding of the distributed architectures of evolving complex systems, and how those can be used to produce artificial intelligence and computational tools, as well as engineering designs, with enhanced robustness, scalability, flexibility and which can interface more effectively with humans. It is a multi-disciplinary field strongly based on biology, physics, complexity, computer science, informatics, cognitive science, robotics, optimization, control, and cybernetics. Bio-inspired computing at the core of modern artificial intelligence, and thus applied throughout science and engineering, but understanding the mechanisms behind resilience, evolvability, and adaptation are essential to tackle the most vexing biomedical and social complexity problems we currently face. Therefore, the course should interest students in various programs. Students will be introduced to fundamental topics in bio-inspired computing and build up their proficiency in the application of various algorithms in real-world problems developed in lab assignments developed for Python (Jupyter) notebooks. 3 credits Prerequisites: Senior level standing or permission of the instructor / department chair. Basic knowledge of Python. Levels: Graduate, Undergraduate

• ISE 485 - Additive Mfg Processes & Sys

  This course aims to inculcate a comprehensive understanding of additive manufacturing (AM), and will address the following consequential aspects of AM: (1) Materials and Process Mechanics; (2) Machines, Machine Design, and Mechanisms; (3) Quality control, Sensing, and Process Monitoring; and (4) Design for AM and novel trans-disciplinary applications. Prerequisites: ISE 311 or permission of the instructor. Crosslisted with SSIE 585. Offered in the Fall semester. 3 credits. Levels: Undergraduate

• ISE 491 - Systems Design

  Covers the design process from the definition of requirements through the final output. Focus is on the design principles and design methodologies used to ensure a quality outcome. Prerequisite: ISE 311 and 362 or consent of department chair. Course fee applies. Refer to the Schedule of Classes. Offered in the Fall semester. 4 credits. Levels: Undergraduate

• ISE 492 - Systems Design Project

  The capstone project for the undergraduate degree. Students are expected to work in multi-disciplinary teams to provide solutions through design. Prerequisite: ISE 491 or consent of department chair. Course fee applies. Offered in the Spring semester. 4 credits. Levels: Graduate, Undergraduate

• ISE 496 - Industrial Internship

  Special topics in industrial and systems engineering. Semester offered varies. Credits vary. Levels: Undergraduate

• ISE 497 - Independent Study

  Available every semester. Credits vary. Levels: Undergraduate

• ISE 497A - Independent Study

  Available every semester. Credits vary. Levels: Undergraduate

Please note: There is a mandatory $250 per course fee attached to the two-course sequence ISE 491 (Systems Design) and ISE 492 (Systems Design Project).

Pre-approved tech electives for BS ISE

• Only one non-ISE (SSIE) technical elective may be allowed
• This also applies to students pursuing minors (such as sustainability)

DEPARTMENT / PROGRAM	COURSE NUMBERS
Biomedical Engineering	300-499
Computer Science	300-499
Electrical and Computer Engineering	300-499
Industrial and Systems Engineering	300-499 Non-core courses
Mechanical Engineering	300-499 except ME 372
Systems Science and Industrial Engineering	501-597