Twin Cities campus
 
Twin Cities Campus

Industrial and Systems Engineering B.I.Sy.E.

Industrial and Systems Engineering
College of Science and Engineering
  • Program Type: Baccalaureate
  • Requirements for this program are current for Spring 2020
  • Required credits to graduate with this degree: 122
  • Required credits within the major: 102
  • Degree: Bachelor of Industrial and Systems Engineering
The industrial and systems engineering curriculum combines analytics (optimization, simulation, probability, and statistics) and management (project management, economics, and business) to support the modeling, design, and optimization of systems across a wide range of applications and domains. The program is accredited by the Engineering Accreditation Commission of ABET, www.abet.org.
Program Delivery
This program is available:
  • via classroom (the majority of instruction is face-to-face)
Admission Requirements
Students must complete 9 courses before admission to the program.
Freshmen are usually admitted to pre-major status before admission to this major.
For information about University of Minnesota admission requirements, visit the Office of Admissions website.
Required prerequisites
Mathematics
MATH 1371 - CSE Calculus I [MATH] (4.0 cr)
or MATH 1271 - Calculus I [MATH] (4.0 cr)
or MATH 1571H - Honors Calculus I [MATH] (4.0 cr)
MATH 1272 - Calculus II (4.0 cr)
or MATH 1372 - CSE Calculus II (4.0 cr)
or MATH 1572H - Honors Calculus II (4.0 cr)
Math 2374 and equivs
MATH 2374 - CSE Multivariable Calculus and Vector Analysis (4.0 cr)
or MATH 2263 - Multivariable Calculus (4.0 cr)
or MATH 2573H - Honors Calculus III (4.0 cr)
Required prerequisites
Physical Sciences
Chemistry
CHEM 1061 - Chemical Principles I [PHYS] (3.0 cr)
or CHEM 1071H - Honors Chemistry I [PHYS] (3.0 cr)
CHEM 1065 - Chemical Principles I Laboratory [PHYS] (1.0 cr)
or CHEM 1075H - Honors Chemistry I Laboratory [PHYS] (1.0 cr)
Physics
PHYS 1301W - Introductory Physics for Science and Engineering I [PHYS, WI] (4.0 cr)
or PHYS 1401V - Honors Physics I [PHYS, WI] (4.0 cr)
PHYS 1302W - Introductory Physics for Science and Engineering II [PHYS, WI] (4.0 cr)
or PHYS 1402V - Honors Physics II [PHYS, WI] (4.0 cr)
Required prerequisites
Introduction ISyE Courses
IE 1101 - Foundations of Industrial and Systems Engineering (4.0 cr)
IE 2021 - Engineering Economics (4.0 cr)
General Requirements
All students in baccalaureate degree programs are required to complete general University and college requirements including writing and liberal education courses. For more information about University-wide requirements, see the liberal education requirements. Required courses for the major, minor or certificate in which a student receives a D grade (with or without plus or minus) do not count toward the major, minor or certificate (including transfer courses).
Program Requirements
All freshmen in the College of Science and Engineering must complete CSE 1001: First-Year Experience.
Non-ISyE Required Courses
CSCI 1133 - Introduction to Computing and Programming Concepts (4.0 cr)
ECON 1101 - Principles of Microeconomics [SOCS, GP] (4.0 cr)
Linear Algebra and Differential Equations
MATH 2373 - CSE Linear Algebra and Differential Equations (4.0 cr)
or MATH 2243 - Linear Algebra and Differential Equations (4.0 cr)
or MATH 2574H - Honors Calculus IV (4.0 cr)
Select from one of the following courses
Take 1 or more course(s) from the following:
· ACCT 3001 - Introduction to Management Accounting (3.0 cr)
· FINA 3001 - Finance Fundamentals (3.0 cr)
· IDSC 3001 - Introduction to Information Technology in Business (3.0 cr)
· MGMT 3001 - Fundamentals of Management (3.0 cr)
· MKTG 3001 - Principles of Marketing (3.0 cr)
· SCO 3001 - Supply Chain and Operations (3.0 cr)
ISyE Courses
IE 3521 - Statistics, Quality, and Reliability (4.0 cr)
IE 3011 - Optimization I (4.0 cr)
IE 3553 - Simulation (4.0 cr)
IE 4011 - Stochastic Models (4.0 cr)
IE 3522 - Quality Engineering and Reliability (4.0 cr)
IE 4551 - Production and Inventory Control (4.0 cr)
IE 3012 - Optimization II (4.0 cr)
IE 4511 - Human Factors (4.0 cr)
IE 4541W - Project Management [WI] (4.0 cr)
IE 4041W - Senior Design [WI] (4.0 cr)
Upper Division Writing Intensive within the major
Students are required to take one upper division writing intensive course within the major. If that requirement has not been satisfied within the core major requirements, students must choose one course from the following list. Some of these courses may also fulfill other major requirements.
Take 0 - 1 course(s) from the following:
· IE 4041W - Senior Design [WI] (4.0 cr)
· IE 4541W - Project Management [WI] (4.0 cr)
Technical Electives
Technical Electives
Take 15 or more credit(s) from the following:
· MATH 4707 - Introduction to Combinatorics and Graph Theory (4.0 cr)
· ACCT 3001 - Introduction to Management Accounting (3.0 cr)
· AEM 3031 - Deformable Body Mechanics (3.0 cr)
· CEGE 3201 - Transportation Engineering (3.0 cr)
· CEGE 4211 - Traffic Engineering (3.0 cr)
· CHEM 4501 - Introduction to Thermodynamics, Kinetics, and Statistical Mechanics (3.0 cr)
· CSCI 4011 - Formal Languages and Automata Theory (4.0 cr)
· CSCI 4041 - Algorithms and Data Structures (4.0 cr)
· CSCI 5521 - Introduction to Machine Learning (3.0 cr)
· CSCI 5523 - Introduction to Data Mining (3.0 cr)
· EE 3005 - Fundamentals of Electrical Engineering (4.0 cr)
· ESPM 3605 - Recycling: Extending Raw Materials [TS] (3.0 cr)
· ESPM 3607 - Natural Resources Consumption and Sustainability [GP] (3.0 cr)
· FINA 3001 - Finance Fundamentals (3.0 cr)
· HINF 5430 - Foundations of Health Informatics I (3.0 cr)
· IDSC 3001 - Introduction to Information Technology in Business (3.0 cr)
· IDSC 3103 - Data Modeling and Databases (2.0 cr)
· IDSC 3104 - Enterprise Systems (2.0 cr)
· IDSC 4444 - Descriptive and Predictive Analytics (2.0 cr)
· IE 3041 - Industrial Assignment I (2.0 cr)
· IE 4043W - Industrial Assignment II [WI] (4.0 cr)
· IE 4044 - Industrial Assignment III (2.0 cr)
· IE 4894H - Senior Honors Thesis (2.0 cr)
· IE 5080 - Topics in Industrial Engineering (1.0-4.0 cr)
· IE 5111 - Systems Engineering I (2.0 cr)
· IE 5113 - Systems Engineering II (4.0 cr)
· IE 5441 - Financial Decision Making (4.0 cr)
· IE 5545 - Decision Analysis (4.0 cr)
· IE 5561 - Analytics and Data-Driven Decision Making (4.0 cr)
· MATH 3283W - Sequences, Series, and Foundations: Writing Intensive [WI] (4.0 cr)
· MATH 4242 - Applied Linear Algebra (4.0 cr)
· MATH 4603 - Advanced Calculus I (4.0 cr)
· MATS 3011 - Introduction to Materials Science and Engineering (3.0 cr)
· ME 3331 - Thermodynamics (3.0 cr)
· MGMT 3001 - Fundamentals of Management (3.0 cr)
· MGMT 3010 - Introduction to Entrepreneurship (4.0 cr)
· MGMT 4040 - Negotiation Strategies (4.0 cr)
· MGMT 4050 - Managing Innovation and Change In Action (2.0 cr)
· MGMT 4172 - Entrepreneurship in Action II (4.0 cr)
· MGMT 5102 - StartUp: Customer Development and Testing (2.0 cr)
· MKTG 3001 - Principles of Marketing (3.0 cr)
· MM 3001W - Manufacturing in the Global Economy [WI] (3.0 cr)
· MM 3305 - Advanced 3D Printing for Innovative Business Practices (3.0 cr)
· MM 4039 - The Science of Sourcing: Partnerships for Success (3.0 cr)
· MOT 4001 - Leadership, Professionalism and Business Basics for Engineers (2.0 cr)
· PDES 5701 - User-Centered Design Studio (3.0 cr)
· PDES 3704 - Computer-Aided Design 1: Solid Modeling and Rendering (3.0 cr)
· PDES 3711 - Product Innovation Lab (4.0 cr)
· PUBH 6717 - Decision Analysis for Health Care (2.0 cr)
· SCO 3001 - Supply Chain and Operations (3.0 cr)
· SCO 3045 - Sourcing and Supply Management (2.0 cr)
· SCO 3048 - Transportation and Logistics Management (2.0 cr)
· SCO 3051 - Service Management (2.0 cr)
· SCO 3056 - Supply Chain Planning and Control (4.0 cr)
· SCO 3072 - Managing Technologies in the Supply Chain (2.0 cr)
· STAT 3022 - Data Analysis (4.0 cr)
· STAT 3032 - Regression and Correlated Data (4.0 cr)
· STAT 4101 - Theory of Statistics I (4.0 cr)
· STAT 4102 - Theory of Statistics II (4.0 cr)
· STAT 5101 - Theory of Statistics I (4.0 cr)
· STAT 5102 - Introduction to Statistical Learning (4.0 cr)
· STAT 5201 - Sampling Methodology in Finite Populations (3.0 cr)
· STAT 5302 - Applied Regression Analysis (4.0 cr)
· STAT 5401 - Applied Multivariate Methods (3.0 cr)
· STAT 5421 - Analysis of Categorical Data (3.0 cr)
· MGMT 4171W - Entrepreneurship in Action I [WI] (4.0 cr)
· IE 5524 - Process Transformation through Lean Tools (2.0 cr)
Program Sub-plans
A sub-plan is not required for this program.
Integrated B.ISyE/MS.ISyE
Courses that will be used to fulfill Masterís degree requirements must appear in this sub-plan by the tenth day of the semester in which the student is enrolled in the courses. Any final edits or updates to this sub-pan must be reflected on the APAS no later than the last day of instruction in the semester in which the undergraduate degree will be awarded. Courses not in this sub-plan by that time cannot be updated at a later time; and, therefore will not be eligible for use towards the Masterís degree.
Integrated B.ISyE/MS.ISyE Required Courses
STAT 5302 - Applied Regression Analysis (4.0 cr)
IE 5561 - Analytics and Data-Driven Decision Making (4.0 cr)
CSCI 5521 - Introduction to Machine Learning (3.0 cr)
or CSCI 5523 - Introduction to Data Mining (3.0 cr)
 
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· College of Science and Engineering

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· Ind. & Systems Engr. B.I.Sy.E. Sample Plan
· Integrated B.ISyE/MS.ISyE Plan Sample Plan

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· Industrial and Systems Engineering B.I.Sy.E.
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MATH 1371 - CSE Calculus I (MATH)
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 1142/1271/1281/1371/1571H
Typically offered: Every Fall & Spring
Differentiation of single-variable functions, basics of integration of single-variable functions. Applications: max-min, related rates, area, curve-sketching. Use of calculator, cooperative learning. prereq: CSE or pre-bioprod concurrent registration is required (or allowed) in biosys engn (PRE), background in [precalculus, geometry, visualization of functions/graphs], instr consent; familiarity with graphing calculators recommended
MATH 1271 - Calculus I (MATH)
Credits: 4.0 [max 4.0]
Course Equivalencies: 00067 - Math 1271/Math 1281/Math 1371/
Typically offered: Every Fall, Spring & Summer
Differential calculus of functions of a single variable, including polynomial, rational, exponential, and trig functions. Applications, including optimization and related rates problems. Single variable integral calculus, using anti-derivatives and simple substitution. Applications may include area, volume, work problems. prereq: 4 yrs high school math including trig or satisfactory score on placement test or grade of at least C- in [1151 or 1155]
MATH 1571H - Honors Calculus I (MATH)
Credits: 4.0 [max 4.0]
Course Equivalencies: 00067 - Math 1142/1271/1281/1371/1571H
Grading Basis: A-F only
Typically offered: Every Fall
Differential/integral calculus of functions of a single variable. Emphasizes hard problem-solving rather than theory. prereq: Honors student and permission of University Honors Program
MATH 1272 - Calculus II
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 1272/1282/1252/1372/1572
Typically offered: Every Fall, Spring & Summer
Techniques of integration. Calculus involving transcendental functions, polar coordinates. Taylor polynomials, vectors/curves in space, cylindrical/spherical coordinates. prereq: [1271 or equiv] with grade of at least C-
MATH 1372 - CSE Calculus II
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 1272/1282/1252/1372/1572
Typically offered: Every Spring
Techniques of integration. Calculus involving transcendental functions, polar coordinates, Taylor polynomials, vectors/curves in space, cylindrical/spherical coordinates. Use of calculators, cooperative learning. prereq: Grade of at least C- in [1371 or equiv], CSE or pre-Bioprod/Biosys Engr
MATH 1572H - Honors Calculus II
Credits: 4.0 [max 4.0]
Course Equivalencies: 00068 - Math 1272/1282/1252/1372/1572
Grading Basis: A-F only
Typically offered: Every Spring
Continuation of 1571. Infinite series, differential calculus of several variables, introduction to linear algebra. prereq: 1571H, honors student, permission of University Honors Program
MATH 2374 - CSE Multivariable Calculus and Vector Analysis
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 2263/2373/2573H/3251
Typically offered: Every Fall & Spring
Derivative as linear map. Differential/integral calculus of functions of several variables, including change of coordinates using Jacobians. Line/surface integrals. Gauss, Green, Stokes theorems. Use of computer technology. prereq: [1272 or 1282 or 1372 or 1572] w/grade of at least C-, CSE or pre-Bioprod/Biosys Engr
MATH 2263 - Multivariable Calculus
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 2263/2373/2573H/3251
Typically offered: Every Fall, Spring & Summer
Derivative as linear map. Differential/integral calculus of functions of several variables, including change of coordinates using Jacobians. Line/surface integrals. Gauss, Green, Stokes Theorems. prereq: [1272 or 1372 or 1572] w/grade of at least C-
MATH 2573H - Honors Calculus III
Credits: 4.0 [max 4.0]
Course Equivalencies: 00069 - Math 2263/2374/3251
Grading Basis: A-F only
Typically offered: Every Fall
Integral calculus of several variables. Vector analysis, including theorems of Gauss, Green, Stokes. prereq: Math 1572H or Math 2574H, honors student and permission of University Honors Program
CHEM 1061 - Chemical Principles I (PHYS)
Credits: 3.0 [max 3.0]
Course Equivalencies: 01884 - Chem 1061/Chem 1071H
Typically offered: Every Fall, Spring & Summer
Atomic theory, periodic properties of elements. Thermochemistry, reaction stoichiometry. Behavior of gases, liquids, and solids. Molecular/ionic structure/bonding. Organic chemistry and polymers. energy sources, environmental issues related to energy use. Prereq-Grade of at least C- in [1011 or 1015] or [passing placement exam, concurrent registration is required (or allowed) in 1065]; intended for science or engineering majors; concurrent registration is required (or allowed) in 1065; registration for 1065 must precede registration for 1061
CHEM 1071H - Honors Chemistry I (PHYS)
Credits: 3.0 [max 3.0]
Course Equivalencies: 01884 - Chem 1061/Chem 1071H
Grading Basis: A-F only
Typically offered: Every Fall
Advanced introduction to atomic theory. Periodic properties of elements. Behavior of gases, liquids, and solids. Molecular/ionic structure, bonding. Aspects of organic chemistry, spectroscopy, and polymers. Mathematically demanding quantitative problems. Writing for scientific journals. prereq: Honors student, permission of University Honors Program, concurrent registration is required (or allowed) in 1075H; registration for 1075H must precede registration for 1071H
CHEM 1065 - Chemical Principles I Laboratory (PHYS)
Credits: 1.0 [max 1.0]
Course Equivalencies: 01878 - Chem 1065/Chem 1075H
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Basic laboratory skills while investigating physical and chemical phenomena closely linked to lecture material. Experimental design, data collection and treatment, discussion of errors, and proper treatment of hazardous wastes. prereq: concurrent registration is required (or allowed) in 1061
CHEM 1075H - Honors Chemistry I Laboratory (PHYS)
Credits: 1.0 [max 1.0]
Course Equivalencies: 01878 - Chem 1065/Chem 1075H
Grading Basis: A-F only
Typically offered: Every Fall
Develop laboratory skills while investigating physical and chemical phenomena closely linked to lecture material. Experimental design, data collection and treatment, discussion of errors, and the proper treatment of hazardous wastes. Prereq-&1071H, honors student, permission of University Honors Program.
PHYS 1301W - Introductory Physics for Science and Engineering I (PHYS, WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 00078
Typically offered: Every Fall, Spring & Summer
Use of fundamental principles to solve quantitative problems. Motion, forces, conservation principles, structure of matter. Applications to mechanical systems. prereq: concurrent registration is required (or allowed) in Math 1271 or concurrent registration is required (or allowed) in Math 1371 or concurrent registration is required (or allowed) in Math 1571
PHYS 1401V - Honors Physics I (PHYS, WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 00078
Grading Basis: A-F only
Typically offered: Every Fall
Comprehensive, calculus-level general physics. Emphasizes use of fundamental principles to solve quantitative problems. Description of motion, forces, conservation principles. Structure of matter, with applications to mechanical systems.
PHYS 1302W - Introductory Physics for Science and Engineering II (PHYS, WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 00079
Typically offered: Every Fall & Spring
Use of fundamental principles to solve quantitative problems. Motion, forces, conservation principles, fields, structure of matter. Applications to electromagnetic phenomena. prereq: 1301W, concurrent registration is required (or allowed) in Math 1272 or Math 1372 or Math 1572
PHYS 1402V - Honors Physics II (PHYS, WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 00079
Grading Basis: A-F only
Typically offered: Every Spring
Fundamental principles to solve quantitative problems. Description of motion, forces, conservation principles, fields. Structure of matter, with applications to electro-magnetic phenomena. prereq: 1401V, honors student or permission of University Honors Program
IE 1101 - Foundations of Industrial and Systems Engineering
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall
History/development of industrial/systems engineering, operations planning, quality control, human factors, resource management, financial engineering, facility location/layout, optimization, probabilistic/stochastic models, simulation, project management. prereq: [MATH 1372 or equiv], CSE student
IE 2021 - Engineering Economics
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall
Cost/design process, cost estimation models, cash flow analysis, interest rate models, time value of money, evaluation of projects, internal rate of return, depreciation/income taxes, price changes/inflation, capital budgeting, decision making under uncertainty. prereq: [MATH 1372 or equiv], CSE student
CSCI 1133 - Introduction to Computing and Programming Concepts
Credits: 4.0 [max 4.0]
Course Equivalencies: 02133 - CSci 1133/CSci 1133H
Typically offered: Every Fall, Spring & Summer
Fundamental programming concepts using Python language. Problem solving skills, recursion, object-oriented programming. Algorithm development techniques. Use of abstractions/modularity. Data structures/abstract data types. Develop programs to solve real-world problems. prereq: concurrent registration is required (or allowed) in MATH 1271 or concurrent registration is required (or allowed) in MATH 1371 or concurrent registration is required (or allowed) in MATH 1571H or instr consent
ECON 1101 - Principles of Microeconomics (SOCS, GP)
Credits: 4.0 [max 4.0]
Course Equivalencies: Econ 1101/1104/1111/ApEc 1101
Typically offered: Every Fall, Spring & Summer
Microeconomic behavior of consumers, firms, and markets in domestic and world economy. Demand and supply. Competition and monopoly. Distribution of income. Economic interdependencies in the global economy. Effects of global linkages on individual decisions. prereq: knowledge of plane geometry and advanced algebra
MATH 2373 - CSE Linear Algebra and Differential Equations
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 2243/2373/2573
Typically offered: Every Fall & Spring
Linear algebra: basis, dimension, eigenvalues/eigenvectors. Differential equations: linear equations/systems, phase space, forcing/resonance, qualitative/numerical analysis of nonlinear systems, Laplace transforms. Use of computer technology. prereq: [1272 or 1282 or 1372 or 1572] w/grade of at least C-, CSE or pre-Bio Prod/Biosys Engr
MATH 2243 - Linear Algebra and Differential Equations
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 2243/2373/2573
Typically offered: Every Fall, Spring & Summer
Linear algebra: basis, dimension, matrices, eigenvalues/eigenvectors. Differential equations: first-order linear, separable; second-order linear with constant coefficients; linear systems with constant coefficients. prereq: [1272 or 1282 or 1372 or 1572] w/grade of at least C-
MATH 2574H - Honors Calculus IV
Credits: 4.0 [max 4.0]
Course Equivalencies: 00561 - Math 2243/Math 2373/Math 2573H
Grading Basis: A-F only
Typically offered: Every Spring
Advanced linear algebra, differential equations. Additional topics as time permits. prereq: Math 1572H or Math 2573H, honors student and permission of University Honors Program
ACCT 3001 - Introduction to Management Accounting
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Costing techniques, including activity-based costing. Applying costing methods to determine costs of products, services, and production processes. Use of costs in operating/strategic decisions. prereq: 2050
FINA 3001 - Finance Fundamentals
Credits: 3.0 [max 3.0]
Course Equivalencies: 00196
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Financial management principles. Money/capital markets, risk/return/valuation triad, capital budgeting. Capital structure, financial leverage. Cost of capital, financial performance measures, dividend policy, working capital management, international financial management/derivatives. prereq: ACCT 2050, SCO 2550 or equivalent statistics course
IDSC 3001 - Introduction to Information Technology in Business
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Developing/using IS to support business processes, managerial decision making, and organizational strategy. Technology components of IS. Impact on organizations. Creation/change processes. Managerial issues. Techniques for designing, developing, and implementing IS. Databases and user interfaces. Computer/communications network platforms. Internet, e-business, and e-commerce applications.
MGMT 3001 - Fundamentals of Management
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Aspects/characteristics of organizations, their members. Why people/groups feel/behave as they do. Processes/methods that improve behavior/attitudes/effectiveness of members. Member/manager skills. Guest speakers, group presentations, films.
MKTG 3001 - Principles of Marketing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Introduction to terms, concepts, and skills for analyzing marketing problems. Factors outside the organization affecting its product, pricing, promotion, and distribution decisions. Cases from actual organizations. prereq: ECON 1101
SCO 3001 - Supply Chain and Operations
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Managing the operations function within manufacturing and service organizations, and across the supply chains of these organizations. The supply chain is the set of organizations and the work that they complete to collectively create customer-valued goods and services. Course emphasizes decision making in work processes, including decision related to managing processes, quality, capacity, inventory, and supply chain activities. Quantitative and qualitative methods are used for improving management of operations.
IE 3521 - Statistics, Quality, and Reliability
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Random variables/probability distributions, statistical sampling/measurement, statistical inferencing, confidence intervals, hypothesis testing, single/multivariate regression, design of experiments, statistical quality control, quality management, reliability, maintainability. prereq: MATH 1372 or equiv
IE 3011 - Optimization I
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall
Optimization models, data/solutions, linear programming, simplex method, duality theory, sensitivity analysis, network optimization models, integer programming. prereq: 1101, MATH 2374, MATH 2373, Upper Division CSE
IE 3553 - Simulation
Credits: 4.0 [max 4.0]
Course Equivalencies: 01915 - IE 3553/IE 5553
Grading Basis: A-F only
Typically offered: Every Fall
Introduction to techniques/tools of stochastic simulation. Applications from finance/insurance risk. Problems in inventory/queueing. prereq: CSCI 1133, IE 3521, ISyE major
IE 4011 - Stochastic Models
Credits: 4.0 [max 4.0]
Prerequisites: 3521, MATH 2373, MATH 2374, ISyE major
Grading Basis: A-F only
Typically offered: Every Spring
Models for describing/evaluating random systems. Formulating/analyzing stochastic models for business. Discrete-time/continuous-time Markov chains. Poisson processes. Markovian/non-Markovian queueing theory. Inventory management, manufacturing, reliability. prereq: 3521, MATH 2373, MATH 2374, ISyE major
IE 3522 - Quality Engineering and Reliability
Credits: 4.0 [max 4.0]
Course Equivalencies: 01914
Grading Basis: A-F only
Typically offered: Every Spring
Quality engineering/management, economics of quality. Statistical process control, reliability, maintain ability, availability. prereq: 3521, MATH 2373, MATH 2374, ISyE major
IE 4551 - Production and Inventory Control
Credits: 4.0 [max 4.0]
Course Equivalencies: 01917 - IE 4551/IE 5551
Prerequisites: 3011, 3521, ISyE major
Grading Basis: A-F only
Typically offered: Every Spring
Methods for managing production, inventory, supply chain operations. Demand forecasting, inventory control, production planning/scheduling, supply chain coordination, manufacturing flow analysis. Implications of emerging technologies, business practices, government regulations. prereq: 3011, 3521, ISyE major
IE 3012 - Optimization II
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Classifying optimization models. Modeling binary variables, branch and bound. Shortest path. Minimum spanning tree. Nonlinear programming, global and local optima, optimality conditions. Algebraic modeling languages and optimization solvers. prereq: 3011, ISyE major
IE 4511 - Human Factors
Credits: 4.0 [max 4.0]
Course Equivalencies: 01553 - HumF 5211/IE 5511/ME 5211
Grading Basis: A-F only
Typically offered: Every Fall
Human factors engineering (ergonomics), methods engineering, work measurement. Human-machine interface: displays, controls, instrument layout, supervisory control. Anthropometry, work physiology/biomechanics. Work environmental factors. Methods engineering. prereq: ISyE senior
IE 4541W - Project Management (WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 01916
Grading Basis: A-F only
Typically offered: Every Fall
Introduction to engineering project management. Analytical methods of selecting, organizing, budgeting, scheduling, and controlling projects. Risk management, team leadership, program management. prereq: ISyE senior
IE 4041W - Senior Design (WI)
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Work in small teams to address open-ended problem in industrial/systems engineering. Teams work with faculty or industry advisers. Project, midterm/final presentation, final report. prereq: 1101, 2021, 3012, 3522, 3553, 4011, 4511, 4541W, 3521, 4551, ISyE senior
IE 4041W - Senior Design (WI)
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Work in small teams to address open-ended problem in industrial/systems engineering. Teams work with faculty or industry advisers. Project, midterm/final presentation, final report. prereq: 1101, 2021, 3012, 3522, 3553, 4011, 4511, 4541W, 3521, 4551, ISyE senior
IE 4541W - Project Management (WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 01916
Grading Basis: A-F only
Typically offered: Every Fall
Introduction to engineering project management. Analytical methods of selecting, organizing, budgeting, scheduling, and controlling projects. Risk management, team leadership, program management. prereq: ISyE senior
MATH 4707 - Introduction to Combinatorics and Graph Theory
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Existence, enumeration, construction, algorithms, optimization. Pigeonhole principle, bijective combinatorics, inclusion-exclusion, recursions, graph modeling, isomorphism. Degree sequences and edge counting. Connectivity, Eulerian graphs, trees, Euler's formula, network flows, matching theory. Mathematical induction as proof technique. prereq: 2243, [2283 or 3283]
ACCT 3001 - Introduction to Management Accounting
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Costing techniques, including activity-based costing. Applying costing methods to determine costs of products, services, and production processes. Use of costs in operating/strategic decisions. prereq: 2050
AEM 3031 - Deformable Body Mechanics
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Uniaxial loading/deformation. Stress/strain at point, Mohr's circle. Internal forces in beams. Material behavior, linear elasticity. Torsion of circular shafts. Bending of beams of symmetrical section. Column buckling. Statically indeterminate structures. prereq: [2011 or 2021 or [BMEN 3011, BMEN major]], [Math 2374 or equiv], [concurrent registration is required (or allowed) in Math 2373 or equiv], CSE
CEGE 3201 - Transportation Engineering
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Applying laws of motion to vehicle performance, determining constraints for highway designs. Traffic flow principles, their relation to capacity and level of service. Geometric design, traffic control, pavement design, transportation planning. prereq: PHYS 1301, (CEGE 3101, CEGE 3102 can be taken concurrently)
CEGE 4211 - Traffic Engineering
Credits: 3.0 [max 3.0]
Course Equivalencies: 02588 - CEGE 4211/CEGE 5211
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Principles of vehicle/driver performance as they apply to safe/efficient operation of highways. Design/use of traffic control devices. Capacity/level of service. Trip generation, traffic impact analysis. Safety/traffic studies. prereq: CEGE 3201, CEGE 3102 or equivalent, upper division CSE or instructor consent
CHEM 4501 - Introduction to Thermodynamics, Kinetics, and Statistical Mechanics
Credits: 3.0 [max 3.0]
Course Equivalencies: 00117 - Chem 3501/4501
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Physical chemistry as it relates to macroscopic descriptions of chemical systems. Chemical thermodynamics, phase equilibria, chemical equilibria. Statistical mechanics. Phenomenological reaction kinetics. Kinetic theory of gases. Collision, statistical theories of reaction rates. prereq: [1062/1066 or 1071H/1075H], [MATH 2263 or concurrent registration is required (or allowed) in MATH 2263 or MATH 2374 or concurrent registration is required (or allowed) in MATH 2374], [PHYS 1302 or PHYS 1402V or PHYS 1502V]
CSCI 4011 - Formal Languages and Automata Theory
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Logical/mathematical foundations of computer science. Formal languages, their correspondence to machine models. Lexical analysis, string matching, parsing. Decidability, undecidability, limits of computability. Computational complexity. prereq: 2041 or instr consent
CSCI 4041 - Algorithms and Data Structures
Credits: 4.0 [max 4.0]
Course Equivalencies: 02015
Typically offered: Every Fall & Spring
Rigorous analysis of algorithms/implementation. Algorithm analysis, sorting algorithms, binary trees, heaps, priority queues, heapsort, balanced binary search trees, AVL trees, hash tables and hashing, graphs, graph traversal, single source shortest path, minimum cost spanning trees. prereq: [(1913 or 1933) and 2011] or instr consent; cannot be taken for grad CSci cr
CSCI 5521 - Introduction to Machine Learning
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Problems of pattern recognition, feature selection, measurement techniques. Statistical decision theory, nonstatistical techniques. Automatic feature selection/data clustering. Syntactic pattern recognition. Mathematical pattern recognition/artificial intelligence. prereq: [[2031 or 2033], STAT 3021] or instr consent
CSCI 5523 - Introduction to Data Mining
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Data pre-processing techniques, data types, similarity measures, data visualization/exploration. Predictive models (e.g., decision trees, SVM, Bayes, K-nearest neighbors, bagging, boosting). Model evaluation techniques, Clustering (hierarchical, partitional, density-based), association analysis, anomaly detection. Case studies from areas such as earth science, the Web, network intrusion, and genomics. Hands-on projects. prereq: 4041 or equiv or instr consent
EE 3005 - Fundamentals of Electrical Engineering
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Fundamentals of analog electronics, digital electronics, and power systems. Circuit analysis, electronic devices and applications, digital circuits, microprocessor systems, operational amplifiers, transistor amplifiers, frequency response, magnetically coupled circuits, transformers, steady state power analysis. prereq: Math 2243, Phys 1302; not for EE majors
ESPM 3605 - Recycling: Extending Raw Materials (TS)
Credits: 3.0 [max 3.0]
Course Equivalencies: 01077
Grading Basis: A-F only
Typically offered: Every Spring
Basic principles of recycling and its role in raw materials utilization, energy, and the environment. Recycling processes for commonly recycled materials, products, and their properties and environmental implications of recycling.
ESPM 3607 - Natural Resources Consumption and Sustainability (GP)
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring
Current world trends for industrial raw materials; environmental/other tradeoffs related to options for satisfying demand/needs; global and systemic thinking; provides a framework for beginning a process of thinking critically about complex environmental problems/potential solutions in a diverse global economy.
FINA 3001 - Finance Fundamentals
Credits: 3.0 [max 3.0]
Course Equivalencies: 00196
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Financial management principles. Money/capital markets, risk/return/valuation triad, capital budgeting. Capital structure, financial leverage. Cost of capital, financial performance measures, dividend policy, working capital management, international financial management/derivatives. prereq: ACCT 2050, SCO 2550 or equivalent statistics course
HINF 5430 - Foundations of Health Informatics I
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
An introductory survey of health informatics, focusing on foundational concepts. Topics covered include: conceptualizations of data, information, and knowledge; current terminologies, coding, and classification systems for medical information; ethics, privacy, and security; systems analysis, process and data modeling; human-computer interaction and data visualization. Lectures, readings, and exercises highlight the intersections of these topics with electronic health record systems and other health information technology. prereq: Junior, senior, grad student, professional student, or instr consent
IDSC 3001 - Introduction to Information Technology in Business
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Developing/using IS to support business processes, managerial decision making, and organizational strategy. Technology components of IS. Impact on organizations. Creation/change processes. Managerial issues. Techniques for designing, developing, and implementing IS. Databases and user interfaces. Computer/communications network platforms. Internet, e-business, and e-commerce applications.
IDSC 3103 - Data Modeling and Databases
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Concepts for designing, using, and implementing database systems. Normalization techniques. Structured Query Language (SQL). Analyzing a business situation. Building a database application.
IDSC 3104 - Enterprise Systems
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Management aspects of Enterprise Systems. Vendor/vendor management options. Technologies, organizational readiness. Hands-on access to software solutions from ERP software provider. End-to-end processes. Measurement of key performance indicators. Analytics, workflow. prereq: 3001
IDSC 4444 - Descriptive and Predictive Analytics
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Spring
Data mining/personalization techniques. Exploratory/ predictive data mining techniques. Data preparation, data visualization, online analytical processing (OLAP), recommender systems. How business analytics techniques are applied in variety of business applications/organizational settings. prereq: 3001
IE 3041 - Industrial Assignment I
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Industrial work assignment in engineering intern program. Evaluation based on student's formal written report covering semester's work assignment. prereq: ISyE upper division, registration in ME co-op program
IE 4043W - Industrial Assignment II (WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: 01311
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Solution of system design problems that require developing criteria, evaluating alternatives, and generating a preliminary design. Final report emphasizes design communication and describes design decision process, analysis, and final recommendations. prereq: 3041
IE 4044 - Industrial Assignment III
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Industrial work assignment in engineering co-op program. Evaluation based on student's formal written report covering semester work assignment. prereq: IE 4043, registration in ME co-op program
IE 4894H - Senior Honors Thesis
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Writing thesis under direction of ISyE faculty member.
IE 5080 - Topics in Industrial Engineering
Credits: 1.0 -4.0 [max 8.0]
Typically offered: Periodic Fall & Spring
Topics vary each semester.
IE 5111 - Systems Engineering I
Credits: 2.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Overview of systems-level thinking/techniques in context of an integrated, design-oriented framework. Elements of systems engineering process, including lifecycle, concurrent, and global engineering. Framework for engineering large-scale, complex systems. How specific techniques fit into framework. prereq: CSE upper div or grad student
IE 5113 - Systems Engineering II
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Systems engineering thinking/techniques presented in 5111. Hands-on techniques applied to specific problems. Topics pertinent to effectiveness of design process. Practices and organizational/reward structure to support collaborative, globally distributed design team.
IE 5441 - Financial Decision Making
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Cash flow streams, interest rates, fixed income securities. Evaluating investment alternatives, capital budgeting, dynamic cash flow process. Mean-variance portfolio selection, Capital Asset Pricing Model, utility maximization, risk aversion. Derivative securities, asset dynamics, basic option pricing theory. prereq: CSE upper div or grad student
IE 5545 - Decision Analysis
Credits: 4.0 [max 4.0]
Typically offered: Periodic Fall & Spring
Single-person and group decision problems. Structuring of decision problems arising in personal, business, and public policy contexts. Decision-making under uncertainty, value of information, games of complete information and Nash equilibrium, Bayesian games, group decision-making and distributed consensus, basics of mechanism design. prereq: 3521 or equiv
IE 5561 - Analytics and Data-Driven Decision Making
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Hands-on experience with modern methods for analytics and data-driven decision making. Methodologies such as linear and integer optimization and supervised and unsupervised learning will be brought together to address problems in a variety of areas such as healthcare, agriculture, sports, energy, and finance. Students will learn how to manipulate data, build and solve models, and interpret and visualize results using a high-level, dynamic programming language. Prerequisites: IE 3521 or equivalent; IE 3011 or IE 5531 or equivalent; proficiency with a programming language such as R, Python, or C.
MATH 3283W - Sequences, Series, and Foundations: Writing Intensive (WI)
Credits: 4.0 [max 4.0]
Course Equivalencies: Math 2283/3283W
Typically offered: Every Fall & Spring
Introduction to reasoning used in advanced mathematics courses. Logic, mathematical induction, real number system, general/monotone/recursively defined sequences, convergence of infinite series/sequences, Taylor's series, power series with applications to differential equations, Newton's method. Writing-intensive component. prereq: [concurrent registration is required (or allowed) in 2243 or concurrent registration is required (or allowed) in 2263 or concurrent registration is required (or allowed) in 2373 or concurrent registration is required (or allowed) in 2374] w/grade of at least C-
MATH 4242 - Applied Linear Algebra
Credits: 4.0 [max 4.0]
Course Equivalencies: 01212 - Math 4242/Math 4457
Typically offered: Every Fall, Spring & Summer
Systems of linear equations, vector spaces, subspaces, bases, linear transformations, matrices, determinants, eigenvalues, canonical forms, quadratic forms, applications. prereq: 2243 or 2373 or 2573
MATH 4603 - Advanced Calculus I
Credits: 4.0 [max 4.0]
Course Equivalencies: 01072 - Math 4606/Math 5615/Math 5616
Typically offered: Every Fall, Spring & Summer
Axioms for the real numbers. Techniques of proof for limits, continuity, uniform convergence. Rigorous treatment of differential/integral calculus for single-variable functions. prereq: [[2243 or 2373], [2263 or 2374]] or 2574 or instr consent
MATS 3011 - Introduction to Materials Science and Engineering
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Builds progressively from electrons to atoms to bonding to crystal structures. Defects, X-ray diffraction, phase diagrams. Microstructure as basis for understanding mechanical/electrical properties. Metals, polymers, ceramics, semiconductors, composites. prereq: CHEM 1061, CHEM 1065, [MATH 1272 or MATH 1372], PHYS 1302, CSE student
ME 3331 - Thermodynamics
Credits: 3.0 [max 3.0]
Course Equivalencies: 01494 - ME 3321/ME 3331
Grading Basis: A-F only
Typically offered: Every Fall, Spring & Summer
Properties, equations of state, processes, cycles for reversible and irreversible thermodynamic systems. Modes of energy transfer. Equations for conservation of mass, energy, entropy balances. Application of thermodynamic principles to modern engineering systems. prereq: Chem 1061, Chem 1065, Phys 1301
MGMT 3001 - Fundamentals of Management
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Aspects/characteristics of organizations, their members. Why people/groups feel/behave as they do. Processes/methods that improve behavior/attitudes/effectiveness of members. Member/manager skills. Guest speakers, group presentations, films.
MGMT 3010 - Introduction to Entrepreneurship
Credits: 4.0 [max 4.0]
Course Equivalencies: 02347
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Fundamentals of entrepreneurship. Career paths, including new business start-ups, franchising, acquisitions (including family business succession), corporate venturing, and entre-preneurial services. Legal structures for new business formation. Aspects of business law/ethics.
MGMT 4040 - Negotiation Strategies
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Securing agreements between two or more parties who are interdependent and seeking to maximize their own outcomes. Behavior of individuals, groups, and organizations in competitive situations.
MGMT 4050 - Managing Innovation and Change In Action
Credits: 2.0 [max 2.0]
Course Equivalencies: 02187 - IBus 4050/Mgmt 4050
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
This course focuses on how entrepreneurs create new businesses and how organizations innovate and change. Special emphasis is given to understanding the sequences of events that typically unfold in individuals, groups, organizations, and industries as innovations develop from concept to implementation. The course relies heavily on the concepts and findings from the Minnesota Innovation Research Program, as well as other studies. The course focuses on how the innovation journey unfolds in the creation of a wide variety of new businesses, technologies, products, programs, and services, and what paths along this journey are likely to lead to success and failure. The course emphasizes building diagnostic skills and developing useful principles that may increase the odds of maneuvering organizational innovation and change journeys. prereq: Mgmt 1001, 3001 or 3010
MGMT 4172 - Entrepreneurship in Action II
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Spring
Second of two-semester sequence. In fall, students identify business opportunity, develop concept, determine resources required, and launch business. In spring, students implement busienss plan, manage business, and determine exit strategy. prereq: 4171
MGMT 5102 - StartUp: Customer Development and Testing
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Provides a structured process with faculty and mentor oversight for students at any level and from any college at the University to learn the initial process of customer development by testing market acceptance of a specific new business concept. Students primarily take this course individually and must have an idea or technology that they are interested in pursuing. The goal of the curse is to teach the process to quickly and efficiently test the value and market fit for a new concept.
MKTG 3001 - Principles of Marketing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Introduction to terms, concepts, and skills for analyzing marketing problems. Factors outside the organization affecting its product, pricing, promotion, and distribution decisions. Cases from actual organizations. prereq: ECON 1101
MM 3001W - Manufacturing in the Global Economy (WI)
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
In this foundation course for manufacturing operations management, you'll find out just how innovative, strategic, and creative manufacturing is. The course is the perfect entry point for students majoring, minoring, or getting a certificate in manufacturing operations management, and it's also a great elective for students seeking a better understanding of the core sector in both U.S. and international economies. The overall objective of MM 3001W is to explore different facets of manufacturing in today's global economy, and the three dimensions of the high-performance manufacturing organization (HPMO) model--leadership, product quality, and innovation--are paramount in that exploration. You'll take a look at past and current Minnesota manufacturing companies (3M and Red Wing Shoes, for example) that are surviving and thriving in today's economy, and also learn why some of those Minnesota companies have failed. As a writing intensive course, MM 3001W also prepares students to be successful writers, both in their coursework at the University of Minnesota and in their future careers, as special attention will be paid to real-world writing applications, skills, and processes. Prerequisites: None.
MM 3305 - Advanced 3D Printing for Innovative Business Practices
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Revolutionize your world with speed and creativity. Three-D printing and additive manufacturing are changing how we work and how manufacturing itself happens. In this course, you'll hone the ability to innovate and to lead others in discovery. The first half of the semester is spent learning how to use additive technology and the second half how it can be applied to real-world industries. By the end of the course, you'll use computer-aided design and the U of M's 3D printing lab to build your own solution to a problem. Join this community of forward-thinking makers and tap some of the most high-tech resources at the U. Prerequisites: None
MM 4039 - The Science of Sourcing: Partnerships for Success
Credits: 3.0 [max 2.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Learn how to maneuver with ease inside the complex network of global manufacturing and outsourcing. The Science of Sourcing is all about setting up a sourcing strategy that hinges on two things: core competencies of your business and, of course, customer satisfaction. By the end of this course, you'll be able to do three things really well: 1) identify which products or processes should be outsourced, 2) perform estimates for cost and comparison of outsourcing options, and finally, 3) execute step-by-step outsourcing as you choose suppliers. You?ll also be exposed to the art of managing an outsourced manufacturer relationship, which includes contracts and performance metrics. It's all about upholding quality and value. Prerequisite: A course such as MM 3001W, or relevant manufacturing experience.
MOT 4001 - Leadership, Professionalism and Business Basics for Engineers
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Elements of business, environment in which technology/business operate. Classes of 15 to 20 students.
PDES 5701 - User-Centered Design Studio
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Spring
This class provides a studio-based overview of user-centered product design and development processes. Students will practice both user and market research, creativity and idea generation tools, concept evaluation/selection techniques, prototyping methods for concept development and communication, and user testing. This class will also cover fundamentals of intellectual property and manufacturing. In this studio, students will apply these skills towards the development of a product concept.
PDES 3704 - Computer-Aided Design 1: Solid Modeling and Rendering
Credits: 3.0 [max 3.0]
Grading Basis: A-F only
Typically offered: Every Fall
This class provides an overview of computer-aided design (CAD) methods for product designers. The primary software covered in this course include Solidworks and Keyshot. These programs are used to make three-dimensional computer generated models of product concepts and render the models to appear photo-realistic. This class may also cover additional 2D and interaction design software.
PDES 3711 - Product Innovation Lab
Credits: 4.0 [max 4.0]
Course Equivalencies: 02649
Grading Basis: A-F only
Typically offered: Every Spring
A hands-on experience in integrated product design and development processes. Elements of industrial design, engineering, business, and humanities are applied to a semester-long product design project. Cross-functional teams of students in different majors work together to design and develop new consumer product concepts with guidance from a community of industry mentors.
PUBH 6717 - Decision Analysis for Health Care
Credits: 2.0 [max 2.0]
Typically offered: Every Fall
Introduction to methods/range of applications of decision analysis and cost-effectiveness analysis in health care technology assessment, medical decision making, and health resource allocation.
SCO 3001 - Supply Chain and Operations
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Managing the operations function within manufacturing and service organizations, and across the supply chains of these organizations. The supply chain is the set of organizations and the work that they complete to collectively create customer-valued goods and services. Course emphasizes decision making in work processes, including decision related to managing processes, quality, capacity, inventory, and supply chain activities. Quantitative and qualitative methods are used for improving management of operations.
SCO 3045 - Sourcing and Supply Management
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
Strategic/operational role of purchasing/supply. Supply management. Supplier-selection criteria such as quantity, quality, cost/price considerations. Buyer-supplier relationships. prereq: 3001
SCO 3048 - Transportation and Logistics Management
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall
Linkages between logistics/transportation and marketing, operations, and finance. How different industries integrate logistics, warehousing, transportation, and information systems. prereq: 3001
SCO 3051 - Service Management
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall
Issues unique to managing service processes. Identifying service needs, designing services, and managing services. prereq: 3001
SCO 3056 - Supply Chain Planning and Control
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Decisions/tradeoffs when directing operations of supply chain. Forecasting, capacity/production planning, just-in-time, theory of constraints, supply chain flows, enterprise resource planning, supply chain design. prereq: 3001 or instr consent
SCO 3072 - Managing Technologies in the Supply Chain
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Spring
Technologies and technological change within/between firms as opportunities for professional leadership. Selecting technologies, nurturing their adoption, and ensuring their exploitation. prereq: 3001
STAT 3022 - Data Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
Practical survey of applied statistical inference/computing covering widely used statistical tools. Multiple regression, variance analysis, experiment design, nonparametric methods, model checking/selection, variable transformation, categorical data analysis, logistic regression. prereq: 3011 or 3021 or SOC 3811
STAT 3032 - Regression and Correlated Data
Credits: 4.0 [max 4.0]
Typically offered: Every Fall & Spring
This is a second course in statistics with a focus on linear regression and correlated data. The intent of this course is to prepare statistics, economics and actuarial science students for statistical modeling needed in their discipline. The course covers the basic concepts of linear algebra and computing in R, simple linear regression, multiple linear regression, statistical inference, model diagnostics, transformations, model selection, model validation, and basics of time series and mixed models. Numerous datasets will be analyzed and interpreted using the open-source statistical software R. prereq: STAT 3011 or STAT 3021
STAT 4101 - Theory of Statistics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Random variables/distributions. Generating functions. Standard distribution families. Data summaries. Sampling distributions. Likelihood/sufficiency. prereq: Math 1272 or Math 1372 or Math 1572H
STAT 4102 - Theory of Statistics II
Credits: 4.0 [max 4.0]
Course Equivalencies: 00260
Typically offered: Every Spring
Estimation. Significance tests. Distribution free methods. Power. Application to regression and to analysis of variance/count data. prereq: STAT 4101
STAT 5101 - Theory of Statistics I
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Logical development of probability, basic issues in statistics. Probability spaces. Random variables, their distributions and expected values. Law of large numbers, central limit theorem, generating functions, multivariate normal distribution. prereq: [Math 2263 or Math 2374 or Math 2573H], [CSCI 2033 or Math 2373 or Math 2243]
STAT 5102 - Introduction to Statistical Learning
Credits: 4.0 [max 4.0]
Course Equivalencies: 00260
Typically offered: Every Spring
Sampling, sufficiency, estimation, test of hypotheses, size/power. Categorical data. Contingency tables. Linear models. Decision theory. prereq: [5101 or Math 5651 or instr consent]
STAT 5201 - Sampling Methodology in Finite Populations
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
Simple random, systematic, stratified, unequal probability sampling. Ratio, model based estimation. Single stage, multistage, adaptive cluster sampling. Spatial sampling. prereq: 3022 or 4102 or 5021 or 5102 or instr consent
STAT 5302 - Applied Regression Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications. prereq: 3032 or 3022 or 4102 or 5021 or 5102 or instr consent
STAT 5401 - Applied Multivariate Methods
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Bivariate and multivariate distributions. Multivariate normal distributions. Analysis of multivariate linear models. Repeated measures, growth curve and profile analysis. Canonical correlation analysis. Principal components and factor analysis. Discrimination, classification, and clustering.
STAT 5421 - Analysis of Categorical Data
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
Varieties of categorical data, cross-classifications, contingency tables. Tests for independence. Combining 2x2 tables. Multidimensional tables/loglinear models. Maximum-likelihood estimation. Tests for goodness of fit. Logistic regression. Generalized linear/multinomial-response models.
MGMT 4171W - Entrepreneurship in Action I (WI)
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall
Two-semester course. In fall, students identify a business oportunity, develop concept, determine resources required, and launch the business. In spring, students implement business plan, manage business, and determine exit strategy. prereq: 3010, [4008 or concurrent registration is required (or allowed) in 4008], completed coursework in business core, CSOM upper division, approved application
IE 5524 - Process Transformation through Lean Tools
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Fall
Lean is a systematic methodology that improves processes by identifying and removing sources of waste in an organization. Lean tools, such as value stream mapping, Kaizen, kanban systems, visual systems, and 5S, improve processes by identifying and removing sources of waste. In this course, you will learn and utilize key Industrial Engineering methodologies to identify opportunities, prioritize these opportunities, develop solutions and create cost models of the solutions effectiveness. Applications of lean process improvement in areas such as manufacturing, healthcare, service operations, and business processes will be considered.
STAT 5302 - Applied Regression Analysis
Credits: 4.0 [max 4.0]
Typically offered: Every Fall, Spring & Summer
Simple, multiple, and polynomial regression. Estimation, testing, prediction. Use of graphics in regression. Stepwise and other numerical methods. Weighted least squares, nonlinear models, response surfaces. Experimental research/applications. prereq: 3032 or 3022 or 4102 or 5021 or 5102 or instr consent
IE 5561 - Analytics and Data-Driven Decision Making
Credits: 4.0 [max 4.0]
Typically offered: Every Spring
Hands-on experience with modern methods for analytics and data-driven decision making. Methodologies such as linear and integer optimization and supervised and unsupervised learning will be brought together to address problems in a variety of areas such as healthcare, agriculture, sports, energy, and finance. Students will learn how to manipulate data, build and solve models, and interpret and visualize results using a high-level, dynamic programming language. Prerequisites: IE 3521 or equivalent; IE 3011 or IE 5531 or equivalent; proficiency with a programming language such as R, Python, or C.
CSCI 5521 - Introduction to Machine Learning
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall
Problems of pattern recognition, feature selection, measurement techniques. Statistical decision theory, nonstatistical techniques. Automatic feature selection/data clustering. Syntactic pattern recognition. Mathematical pattern recognition/artificial intelligence. prereq: [[2031 or 2033], STAT 3021] or instr consent
CSCI 5523 - Introduction to Data Mining
Credits: 3.0 [max 3.0]
Typically offered: Periodic Fall & Spring
Data pre-processing techniques, data types, similarity measures, data visualization/exploration. Predictive models (e.g., decision trees, SVM, Bayes, K-nearest neighbors, bagging, boosting). Model evaluation techniques, Clustering (hierarchical, partitional, density-based), association analysis, anomaly detection. Case studies from areas such as earth science, the Web, network intrusion, and genomics. Hands-on projects. prereq: 4041 or equiv or instr consent