Program Details : University Catalogs : University of Minnesota

MATH 1371 - CSE Calculus I (MATH)

Credits:	4.0 [max 4.0]
Course Equivalencies:	Math 1271/Math 1381/Math 1571/
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:	Math 1271/Math 1381/Math 1571/
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:	Math 1271/Math 1381/Math 1571/
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/Math 1282/Math 1372/
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/Math 1282/Math 1372/
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:	Math 1272/Math 1282/Math 1372/
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

Continuation of 1571. Infinite series, differential calculus of several variables, introduction to linear algebra. prereq: 1571H (or equivalent) honors student

MATH 2374 - CSE Multivariable Calculus and Vector Analysis

Credits:	4.0 [max 4.0]
Course Equivalencies:	Math 2263/Math 2374/Math 2573H
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/Math 2374/Math 2573H
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:	Math 2263/Math 2374/Math 2573H
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 equivalent), honors student

CHEM 1061 - Chemical Principles I (PHYS)

Credits:	3.0 [max 3.0]
Course Equivalencies:	Chem 1061/ 1071/H/ 1081
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:	Chem 1061/ 1071/H/ 1081
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:	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:	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: prereq or coreq 1071H; honors student or permission of University Honors Program

PHYS 1301W - Introductory Physics for Science and Engineering I (PHYS, WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	Phys 1201W/1301W/1401V/1501V
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 or Concurrent: MATH 1271/1371/1371H or equivalent

PHYS 1401V - Honors Physics I (PHYS, WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	Phys 1201W/1301W/1401V/1501V
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. Prereq: Honors program or with permission, Prereq or Concurrent: MATH 1271/1371/1571H or equivalent

PHYS 1302W - Introductory Physics for Science and Engineering II (PHYS, WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	Phys 1202W/1302W/1402V/1502V
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: PHYS 1301 or equivalent, Prereq or Concurrent: MATH 1272/1372/1572H or equivalent

PHYS 1402V - Honors Physics II (PHYS, WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	Phys 1202W/1302W/1402V/1502V
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. Honors program or with permission, PHYS 1401V or equivalent, Prereq or CC: MATH 1272/1372/1572H or equivalent

IE 1101 - Foundations of Industrial and Systems Engineering

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This course will provide you with an introduction to Industrial and Systems Engineering with an emphasis on models and solution methods used in system design, planning, and operation. The course will also provide you with an introduction to important problems Industrial and Systems Engineers solve in systems arising in supply chains, transportation, manufacturing, retail, and healthcare delivery, among others. Additional emphasis will be given to various relevant emerging technologies, business practices, and government regulations. 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:	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 1101/1165 ApEc 1101/1101H
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 2142 - Elementary Linear Algebra

Credits:	4.0 [max 1.0]
Typically offered:	Every Fall & Spring

This course has three primary objectives. (1) To present the basic theory of linear algebra, including: solving systems of linear equations; determinants; the theory of Euclidean vector spaces and general vector spaces; eigenvalues and eigenvectors of matrices; inner products; diagonalization of quadratic forms; and linear transformations between vector spaces. (2) To introduce certain aspects of numerical linear algebra and computation. (3) To introduce applications of linear algebra to other domains such as data science. Objectives (2) and (3) will be taught with hands-on computer projects in a high-level programming language. Prerequisites: MATH 1272 or equivalent

MATH 2373 - CSE Linear Algebra and Differential Equations

Credits:	4.0 [max 4.0]
Course Equivalencies:	Math 2243/Math 2373/Math 2574H
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/Math 2373/Math 2574H
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:	Math 2243/Math 2373/Math 2574H
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 - Strategic Management Accounting

Credits:	3.0 [max 3.0]
Course Equivalencies:	Acct 3001/IBus 3002
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: ACCT 2051 or 2050

FINA 3001 - Finance Fundamentals

Credits:	3.0 [max 3.0]
Course Equivalencies:	ApEc 3501/Fina 3001/Fina 3001H
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

How competition for capital in Capital Markets establishes metrics and measures used to understand financial performance of the firm. The course introduces the finance view of the firm and the application of value creation principles to firm decision making. Course presents the centrality of cash flows, the theoretical foundations for Time Value of Money, decision tools for investment of capital, basic valuation of stocks and bonds, and the theoretical foundations for the impact of risk on the required return on investor capital. prereq: ACCT 2050 or ACCT 2051, SCO 2550 or BA 2551 or equivalent statistics course

IDSC 3001 - Information Systems & Digital Transformation (TS)

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall, Spring & Summer

Information technologies have transformed the way businesses operate and the way consumers interact with businesses. They have enabled organizations to increase efficiency, reduce costs, and reach new customers. Their impact goes beyond the business world and affects nearly every aspect of modern society. Along with the benefits they provide, technologies have created new problems around privacy, security, misinformation on social media, algorithmic bias, and potential stifling of competition and innovation. In today's digital age, it is crucial to develop an understanding of information technologies, their impact on business and society, and the challenges they pose for decision making in commercial firms, government agencies, and public policies. This course is designed to cover a broad range of information technology issues in order to prepare students for the knowledge intensive economy of the 21st century. Students will be exposed to not only the technical aspects of information technologies, but also the social, political, and economic factors that shape its development and use. Through a combination of lectures, discussions, videos, in-class exercises and talks by guest speakers, students will gain an in-depth understanding of how information technologies are shaping businesses and the society as a whole. Students will also develop critical thinking skills to analyze and evaluate the impact of technology on society. Topics include business strategy and disruptive technologies, enterprise systems such as those for Customer Relationship Management, Supply Chain Management and Human Resource Management, electronic and mobile commerce, social media applications and their social impact, cloud computing, data analytics, IT privacy and security, artificial intelligence and its social impact.

MGMT 3001 - Fundamentals of Management

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall, Spring & Summer

This course is about the foundational principles of management, encompassing disciplinary and topical boundaries. We will look at these principles from the perspective of how they guide action, specifically: planning, organizing, leading and controlling. By the end of the course, students will know the basics of how to set up organizations to be effective and innovative, and not just efficient. During the course, you will engage with the material in the course and understand how management frameworks can be used to choose the right internal structures and processes that can best react to your particular industry context and general business environment.

MKTG 3001 - Principles of Marketing

Credits:	3.0 [max 3.0]
Course Equivalencies:	Mktg 3001/Mktg 3001H
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 or ECON 1165

SCO 3001 - Sustainable Supply Chain and Operations

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Sustainable Supply Chain and Operations Management focuses on the design and management of transformation processes to provide products and services to create value for the people, planet, and firm prosperity. On the one hand, supply chain and operations management involves the integration of activities and processes, to facilitate the flows of materials, services, finances, and information to convert inputs into the firms? primary products and services. Operational issues include the design of products and processes, the procurement of raw materials, the control of inventories, the maintenance of quality, the planning of human resources and facilities, and the delivery of products or services, so that customer expectations and needs are met. Operations also have significant interactions with other functional areas of the firm (e.g., finance, marketing, strategy, and accounting). Therefore, understanding the role of the operations function and its impact on the competitiveness of the firm from both tactical and strategic aspects is an important part of any manager's training. This course will introduce students to the fundamental concepts, operations practices, and models in both manufacturing- and service-oriented firms. The course will cover both quantitative and qualitative methods.

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 inference, confidence intervals, hypothesis testing, single/multivariate regression, design of experiments. Applications to statistical quality control and reliability. prereq: MATH 1372 or equiv

IE 3011 - Optimization Models and Methods

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Linear, nonlinear, integer, and network optimization models and their tractability; Sensitivity analysis; Solution with software; Introduction to solution methods; Simplex method and Dijkstra?s algorithm. prereq: MATH 2374, MATH 2142, or equivalent, Upper Division CSE

IE 3553 - Simulation

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 3553/IE 5553
Grading Basis:	A-F only
Typically offered:	Every Fall

This course is an introduction to Monte Carlo and Discrete Event Simulation. Student will learn fundamentals of simulation modeling, including generation of psuedo-random numbers, generation of random variables, input probability distributions, variance reduction techniques, analysis of simulation output, and comparison of system configurations using experimental design. Students will implement simulation models using a software package such as Simio. Applications to problems in manufacturing, service operations, healthcare, finance, and transportation. prereq: CSCI 1133, IE 3521 or equivalent, CSE Upper Division

IE 4011 - Stochastic Models

Credits:	4.0 [max 4.0]
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: MATH 2374, MATH 2142 or MATH 2373 or equivalent, 3521 or Stat 3021, CSE Upper Division

IE 3522 - Quality Engineering and Six Sigma

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 3522/IE 5522
Grading Basis:	A-F only
Typically offered:	Every Spring

Methods for Quality Engineering and Six Sigma, including Statistical Process Control, DMAIC improvement framework, Control Charts, Process Capability, Measurement System Capability, Designed Experiments, and FMEA. prereq: MATH 2374, MATH 2142 or MATH 2373 or equivalent , 3521 or Stat 3021, CSE Upper Division

IE 4551 - Production, Inventory, and Service Operations

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Methods for managing production, inventory, supply chain, and service operations. Demand forecasting, inventory control, production planning/scheduling, supply chain coordination, manufacturing flow analysis, and service waiting line management. Implications of emerging technologies, business practices, and government regulations. prereq: MATH 2374, MATH 2142, or MATH 2373 or equivalent, 3521 or STAT 3021, CSE Upper Division

IE 4511 - Human Factors

Credits:	4.0 [max 4.0]
Course Equivalencies:	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: CSE Upper Division

IE 4541W - Project Management (WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 4541/IE 5541
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

Students work in small teams to address open-ended problems in Industrial and Systems Engineering. Each team works with a faculty advisory and industry mentor. prereq: IE 1101, 2021, 3011, 3521, 3522, 3553, 4011, 4511, 4541W, 4551, ISyE senior

IE 4041W - Senior Design (WI)

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Students work in small teams to address open-ended problems in Industrial and Systems Engineering. Each team works with a faculty advisory and industry mentor. prereq: IE 1101, 2021, 3011, 3521, 3522, 3553, 4011, 4511, 4541W, 4551, ISyE senior

IE 4541W - Project Management (WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	IE 4541/IE 5541
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 5012 - Discrete Optimization Methods and Applications

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Discrete and combinatorial optimization techniques; heuristics; dynamic programming; handling uncertainty in optimization models. Applications in logistics, healthcare, data analysis. (Previously offered as IE 3012.) prereq: (i) MATH 2374, MATH 2142 or MATH 2373 or equivalent, (ii) Upper Division CSE, (iii) CSCI 1133 or equivalent

IE 3013 - Optimization for Machine Learning

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Machine learning has been widely used in areas such as computer vision, search engines, speech recognition, robotics, recommendation systems, bioinformatics, social networks, and finance. It has become an important tool in prediction and data analysis. This course introduces some fundamental solution methods for solving various optimization models arising in the context of machine learning.

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 5513 - Engineering Safety

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Occupational, health, and product safety. Standards, laws, and regulations. Hazards and their engineering control, including general principles, tools and machines, mechanics and structures, electrical safety, materials handling, fire safety, and chemicals. Human behavior and safety, procedures and training, warnings and instructions. prereq: Upper div CSE or grad student

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.

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 5551 - Production and Inventory Systems

Credits:	4.0 [max 4.0]
Typically offered:	Every Spring

Inventory control, supply chain management, demand forecasting, capacity planning, aggregate production and material requirement planning, operations scheduling, and shop floor control. Quantitative models used to support decisions. Implications of emerging information technologies and of electronic commerce for supply chain management and factory operation. prereq: CNR or upper div or grad student

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.

ACCT 3001 - Strategic Management Accounting

Credits:	3.0 [max 3.0]
Course Equivalencies:	Acct 3001/IBus 3002
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: ACCT 2051 or 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

APEC 5721 - Economics of Science and Technology Policy

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

This course covers the economic effects of science and technology policies, such as intellectual property rights. The course considers the effects of policies on: (1) the economic growth and development levels of countries; (2) the international technology transfers that occur between countries through trade, foreign direct investment, and licensing arrangements; and (3) differences in the economic welfare of developed and developing countries. prereq: APEC 3001 or ECON 3101 or instr consent

BLAW 3062 - Contract Law and Corporate Regulation

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

This course highlights topics that are important to any business major, with particular emphasis on publicly-traded companies. NOTE: This course is designed for students who do not have knowledge or experience with any aspect of business law. There is no prerequisite for this course. General topics include: (1) the law of contracts and transactions involving the sale of goods, (2) secured transactions (how creditors can use a debtor?s assets as collateral to secure indebtedness), and (3) the basics of bankruptcy law. Public company subjects include: pros and cons of going public, the IPO process, federal securities laws and SEC regulations regarding public company reporting requirements, insider trading, the Sarbanes-Oxley Act of 2002 and its impact on corporate governance, trends in shareholder democracy rights and shareholder activism, and the role of boards and audit committees. Throughout the course, we will examine the impact of the Supreme Court on American business. NOTE: Students who previously took BLAW 3058 (4 credit course) should NOT take this course.

CEGE 3201 - Transportation Engineering (TS)

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 - Highway Design and Traffic Operations

Credits:	4.0 [max 4.0]
Course Equivalencies:	CEGE 4211/CEGE 5211
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Principles of vehicle/driver performance as they apply to design and operation of highways. Highway alignment and roadside design. Intersection design and traffic control devices. Capacity/level of service. Trip generation and traffic impact analysis. Safety studies and safety impacts of design and operational decisions. 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:	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 3041 - Introduction to Discrete Structures and Algorithms

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall & Spring

Overview of strategies and techniques for the design and analysis of algorithms. Logic and proof techniques, asymptotic notation, recurrences, graphs and relations. Algorithm design strategies and examples from graph algorithms, greedy, divide-and-conquer, and dynamic programming. This course is intended for non-CS Majors. Prerequisite: CSci 2081, concurrent registration with CSci 2081 and upper class standing, or instructor permission.

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:	CSci 4041/CSci 4041H
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 4131 - Internet Programming

Credits:	3.0 [max 3.0]
Course Equivalencies:	CSci 4131/CSci 5131
Typically offered:	Every Fall & Spring

Issues in internet programming. Internet history, architecture/protocols, network programming, Web architecture. Client-server architectures and protocols. Client-side programming, server-side programming, dynamic HTML, Java programming, object-oriented architecture/design, distributed object computing, Web applications. prereq: 4061, 4211 recommended, cannot be taken for grad CSci cr

CSCI 4511W - Introduction to Artificial Intelligence (WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	CSci 4511W/CSci 5511
Typically offered:	Every Fall & Spring

Problem solving, search, inference techniques. Knowledge representation. Planning. Machine learning. Robotics. Lisp programming language. Cannot be taken for grad CSci credit. prereq: 2041 or instr consent

CSCI 4707 - Practice of Database Systems

Credits:	3.0 [max 3.0]
Course Equivalencies:	CSci 4707/CSci 5707/INET 4707
Typically offered:	Every Fall & Spring

Concepts, conceptual data models, case studies, common data manipulation languages, logical data models, database design, facilities for database security/integrity, applications. prereq: 4041 or instr consent

CSCI 5521 - Machine Learning Fundamentals

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, and knowledge of partial derivatives

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

CSCI 5541 - Natural Language Processing

Credits:	3.0 [max 3.0]
Typically offered:	Periodic Spring

Computers are poor conversationalists, despite decades of attempts to change that fact. This course will provide an overview of the computational techniques developed in the attempt to enable computers to interpret and respond appropriately to ideas expressed using natural languages (such as English or French) as opposed to formal languages (such as C++ or Python). Topics in this course will include parsing, semantic analysis, machine translation, dialogue systems, and statistical methods in speech recognition. Suggested prerequisite: CSCI 2041

CSE 4896 - Cooperative Industrial Assignment I

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring & Summer

This course accompanies an industrial work assignment in engineering and applied science. It includes analysis of technical problems that require developing criteria, evaluating alternatives, and completing a final analysis. A final technical design report emphasizes design communication and describes the technical decision process, analysis, and final recommendations. This course is intended for any College of Science and Engineering student who has been admitted to their major and is participating in the co-op program. There are no specific prerequisites for this course, though it is expected that students taking this course have a background in science or engineering appropriate for their industrial co-op position. Registration is by permission only. Please submit your application to the Co-op Program via Handshake to initiate the course access process. Detailed instructions can be found on the co-op website (https://cse.umn.edu/coop/application-process). This is the first course in a two-semester sequence. CSE 4896 is offered in the summer and spring semesters. CSE 4996 is offered in the Summer and fall semesters. It is expected that students complete a co-op experience back-to-back (i.e. summer/fall or spring/summer). If your co-op plan differs from that, please email co-op@umn.edu to receive permission to take the courses in reverse order.

CSE 4996 - Cooperative Industrial Assignment II

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Summer

This course accompanies an industrial work assignment in engineering and applied science. The course includes generation of a novel idea requiring developing criteria, evaluating alternatives, and completing a final analysis. A final invention disclosure report emphasizes innovation and communication and includes the technical creation process, hypothesis testing, analysis, and final recommendations. This is the second course in a two course series. While some content is similar between the courses, the first course focuses more on the design and problem solving in an industrial context, this course focuses on the idea creation process and intellectual property protection. This course also includes a section on diversity, equity and inclusion in corporate settings. This course is intended for any College of Science and Engineering student who has been admitted to their major and is participating in the CSE Co-op Program. There are no specific prerequisites for this course, though it is expected that students taking this course have a background in science or engineering appropriate for their industrial co-op position. Registration is by permission only. Please submit your application to the Co-op Program via Handshake to initiate the course access process. Detailed instructions can be found on the co-op website (https://cse.umn.edu/coop/application-process). This is the second course in a two semester sequence. CSE 4896 is offered in the summer and spring semesters. CSE 4996 is offered in the summer and fall semesters. It is expected that students complete a co-op experience back-to-back (ie. summer/fall or spring/summer). If your co-op plan differs from that, please email co-op@umn.edu to receive permission to take the courses in reverse order.

DES 3131 - User Experience in Design

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Introduction to theories/principles of human interaction with designed objects. Focuses on affect/emotional quality of designs. Objects, interfaces, environments. Digitally mediated experiences.

DES 3141 - Technology, Design, and Society (TS)

Credits:	3.0 [max 3.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Explore/evaluate impact of technology/design on humans, societies. How design innovation shapes cultures. How people use technology to shape design, adoption, use of designed products/environments through consumerism/ethical values.

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

EE 5373 - Data Modeling Using R

Credits:	1.0 [max 1.0]
Grading Basis:	A-F only
Typically offered:	Periodic Fall & Spring

Introduction to data modeling and the R language programming. Multi-factor linear regression modeling. Residual analysis and model quality evaluation. Response prediction. Training and testing. Integral lab. An introductory course in probability and statistics is suggested but not required; basic programming skills in some high-level programming language, such as C/C++, Java, Fortran, etc also suggested.

ESPM 3011W - Ethics in Natural Resources (CIV, WI)

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

Normative/professional ethics, and leadership considerations, applicable to managing natural resources and the environment. Readings, discussion.

ESPM 3221 - Soil Conservation and Land-Use Management

Credits:	3.0 [max 3.0]
Typically offered:	Every Spring

This course is designed to provide a local and global historical perspective of soil erosion (causes and consequences); develop a scientific understanding of soil erosion processes; and relates various soil conservation and land-use management strategies to real-world situations. Basics of soil erosion processes and prediction methods will be the fundamental building blocks of this course. From this understanding, we will discuss policies and socioeconomic aspects of soil erosion. Lastly, we will focus on effective land-use management using natural resource assessment tools. Case studies and real-world and current events examples will be used throughout the course to relate course material to experiences. prereq: SOIL 2125 or instr consent

ESPM 3241W - Natural Resource and Environmental Policy (SOCS, CIV, WI)

Credits:	3.0 [max 3.0]
Course Equivalencies:	ESPM 3241W/ESPM 5241
Typically offered:	Every Spring

Political processes in management of the environment. How disagreements are addressed by different stakeholders, private-sector interests, government agencies, institutions, communities, and nonprofit organizations.

ESPM 3245 - Sustainable Land Use Planning and Policy (ENV)

Credits:	3.0 [max 3.0]
Course Equivalencies:	ESPM 3245/ESPM 5245
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Policies affecting land use planning at local, state, and federal levels. Ecosystem and landscape scale planning. Collaborative and community-based approaches to planning for ecological, social, and economic sustainability. Class project applies interdisciplinary perspectives on planning and policy, including information gathering techniques, conservation planning tools, and evaluation of planning options.

ESPM 3261 - Economics and Natural Resources Management (SOCS, ENV)

Credits:	4.0 [max 4.0]
Course Equivalencies:	ESPM 3261/ESPM 5261
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Microeconomic principles and their application to natural resource management problems. Economic and policy tools to address market failures. Discussion of regulatory and market-based instruments. Discounting and compounding concepts. Methods for conducting financial and economic analyses of natural resource management projects. Decision criteria when conducting benefit/cost analysis of natural resource projects. Methods for valuing non-market natural resource goods and services. Economics of managing renewable natural resources such as forests and fisheries. Land economics. Payments for environmental services. Planning and management problems. Case studies. prereq: MATH 1031 or equivalent.

ESPM 3271 - Environmental Policy, Law, and Human Behavior (CIV, SOCS)

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

What is necessary to achieve sustainable societies. What influences societal deliberation/decisions about environmental issues. How our behaviors affect natural systems. Key theoretical concepts of environmental social psychology and political science. How people respond to policies, using theoretical concepts from social psychology about attitudes, values, and social norms; applying these ideas to specific environmental problems and ethical debates.

ESPM 3602 - Regulations and Corporate Environmental Management

Credits:	3.0 [max 3.0]
Course Equivalencies:	ESPM 3602/ESPM 5602
Grading Basis:	A-F only
Typically offered:	Every Spring

Concepts/issues relating to industrial ecology and industry as they are influenced by current standards/regulations at local, state, and national levels. prereq: APEC 1101 or ECON 1101 or 3261W

ESPM 3603 - Environmental Life Cycle Analysis

Credits:	3.0 [max 3.0]
Course Equivalencies:	ESPM 3603/ESPM 5603
Grading Basis:	A-F only
Typically offered:	Every Fall

Concepts/issues relating to inventory, subsequent analysis of production systems. Production system from holistic point of view, using term commonly used in industrial ecology: "metabolic system."

ESPM 3604 - Environmental Management Systems and Strategy

Credits:	3.0 [max 3.0]
Course Equivalencies:	ESPM 3604/ESPM 5604
Grading Basis:	A-F only
Typically offered:	Every Fall

Environmental problems such as climate change, ozone depletion, and loss of biodiversity.

ESPM 3605 - Recycling: Extending Raw Materials (TS)

Credits:	3.0 [max 3.0]
Course Equivalencies:	ESPM 3605/ESPM 5605
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.

ESPM 4061W - Water Quality and Natural Resources (ENV, WI)

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Water quality decision making. International focus. Ecology of aquatic ecosystems, how they are valuable to society and changed by landscape management. Case studies, impaired waters, TMDL process, student engagement in simulating water quality decision making.

FINA 3001 - Finance Fundamentals

Credits:	3.0 [max 3.0]
Course Equivalencies:	ApEc 3501/Fina 3001/Fina 3001H
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

How competition for capital in Capital Markets establishes metrics and measures used to understand financial performance of the firm. The course introduces the finance view of the firm and the application of value creation principles to firm decision making. Course presents the centrality of cash flows, the theoretical foundations for Time Value of Money, decision tools for investment of capital, basic valuation of stocks and bonds, and the theoretical foundations for the impact of risk on the required return on investor capital. prereq: ACCT 2050 or ACCT 2051, SCO 2550 or BA 2551 or equivalent statistics course

FINA 4221 - Principles of Corporate Finance

Credits:	2.0 [max 2.0]
Course Equivalencies:	Fina 4221/Fina 4241
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

This course evaluates how the financing choices the firm makes influence the creation of firm value and allocation of firm risks among investors. Course presents the debt vs. equity trade-off, tax effects of financing, dividend vs. share repurchases, and the impact on managerial incentives and agency problems. prereq: 3001 or 3001H, CSOM major or Math/Actuarial Science major or Management Minor

GCC 3027 - Power Systems Journey: Making the Invisible Visible and Actionable (TS)

Credits:	3.0 [max 3.0]
Course Equivalencies:	GCC 3027/GCC 5027
Grading Basis:	A-F only
Typically offered:	Periodic Fall

An energy revolution is underway, and needs to accelerate to support climate and economic goals. But the general citizenry does not understand our current energy systems, particularly the seemingly invisible phenomena of electricity, and its generation, distribution, and use. Technical knowledge is only half the solution, however. It is through human decisions and behaviors that technical solutions get applied and adopted, and the importance of communication and storytelling is being recognized for its relevance to making change. How can science literacy and behavior-motivating engagement and storytelling be combined to help make systemic change? This course explores the integration of science-based environmental education, with art-led, place-based exploration of landscapes and creative map-making to address this challenge. How do we make electricity visible, understandable, and interesting -- so we can engage citizens in energy conservation with basic literacy about the electric power system so that they can be informed voters, policy advocates, and consumers. In this class, you will take on this challenge, first learning about the electric power systems you use, their cultural and technical history, systems thinking, design thinking, and prior examples of communication and education efforts. With this foundation, you will then apply your learning to create a public education project delivered via online GIS Story maps that use a combination of data, art, and story to help others understand, and act on the power journey we are all on. All will share the common exploration of power systems through field trips, and contribute to a multi-faceted story of power, presented in a group map and individual GIS Story maps. No prior knowledge of GIS story maps or electricity issues is needed. The study of power systems can be a model for learning and communicating about other topics that explore the interaction of technology and society toward sustainability. This is a Grand Challenge Curriculum course. GCC courses are open to all students and fulfill an honors experience for University Honors Program students.

HINF 5430 - Foundations of Health Informatics I

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

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

HINF 5510 - Applied Health Care Databases: Database Principles and Data Evaluation

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Principles of database theory, modeling, design, and manipulation of databases will be introduced, taught with a healthcare applications emphasis. Students will gain experience using a relational database management system (RDBMS), and database manipulation will be explored using Structured Query Language (SQL) to compose and execute queries. Students will be able to critically evaluate database query methods and results, and understand their implications for health care. prereq: Junior or senior or grad student or professional student or instr consent

HINF 5531 - Health Data Analytics and Data Science

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

Data science methods and techniques for the extraction, preparation, and use of health data in decision making. prereq: Junior or senior or professional student or grad student or instr consent

HSM 3521 - Health Care Delivery Systems

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

Health care (HC) delivery systems, health economics, third-party/public reimbursement, current trends in HC organizations/management/administration. Regulations, standards, quality assurance, accreditation, current ethical issues. Implications for HC providers/professionals, patients/families, communities, international health. prereq: 30 cr

HSM 4541 - Health Care Finance

Credits:	3.0 [max 3.0]
Course Equivalencies:	HSM 4541/HSM 6541
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

General principles of financial management for health care industry. Operational knowledge of financial management theory, esp., how hospitals and their departments develop/balance operating/capital budget for business growth/development. Governmental policies, procedures, and ethical issues controlling the health care industry. prereq: Basic accounting knowledge, a course such as ACCT 2050, and knowledge of Microsoft Excel are strongly recommended. HSM pre-majors should wait for major status to take this course.

HSM 4561W - Health Care Administration and Management (WI)

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Knowledge and and skills in the organizational and managerial aspects of health care. Applications of behavioral and organizational theory to health care settings. Topics will include organization models, supervision, employee evaluation, problem solving, productivity management, group leadership, and case studies. As a Writing Intensive course, it will provide management-level communication skills to develop a thoughtful and reflective understanding of the writing (and rewriting) process.

HSM 4575 - Innovation in Health Services

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall

This interactive course will help you understand the theory and practical application of innovation to solve big challenges in the health care system. You will learn and apply multiple approaches and tools for innovation and human-centered design to reshape organizational culture, strategy, structures, and systems.

IDSC 3001 - Information Systems & Digital Transformation (TS)

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall, Spring & Summer

Information technologies have transformed the way businesses operate and the way consumers interact with businesses. They have enabled organizations to increase efficiency, reduce costs, and reach new customers. Their impact goes beyond the business world and affects nearly every aspect of modern society. Along with the benefits they provide, technologies have created new problems around privacy, security, misinformation on social media, algorithmic bias, and potential stifling of competition and innovation. In today's digital age, it is crucial to develop an understanding of information technologies, their impact on business and society, and the challenges they pose for decision making in commercial firms, government agencies, and public policies. This course is designed to cover a broad range of information technology issues in order to prepare students for the knowledge intensive economy of the 21st century. Students will be exposed to not only the technical aspects of information technologies, but also the social, political, and economic factors that shape its development and use. Through a combination of lectures, discussions, videos, in-class exercises and talks by guest speakers, students will gain an in-depth understanding of how information technologies are shaping businesses and the society as a whole. Students will also develop critical thinking skills to analyze and evaluate the impact of technology on society. Topics include business strategy and disruptive technologies, enterprise systems such as those for Customer Relationship Management, Supply Chain Management and Human Resource Management, electronic and mobile commerce, social media applications and their social impact, cloud computing, data analytics, IT privacy and security, artificial intelligence and its social impact.

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 4110 - Data Engineering for Business Analytics

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Modern organizations increasingly base their decisions on data which is becoming more abundant by each day. The first step of using data for decision making is to prepare data in a suitable format for analysis, a step commonly known as data engineering. Typical data engineering tasks may include data acquisition, parsing, handling missing data, summarization, augmenting, transformation, subsetting, sampling, aggregation, and merging. Data engineers also frequently use basic data visualization tools to detect and fix data issues. Most recently, there is increasing demand for data engineers to handle big data and unstructured data. A good data engineering process ensures quality, reliability, and usability of data. In fact, data engineering is such a critical and time-consuming step of data-driven decision making that many data scientists and analysts spend more than 60% of their time doing data engineering related tasks.

IDSC 4210 - Interactive Data Visualization for Business Analytics

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

IDSC 4210 is an elective course for the undergraduate Business Analytics minor at the Carlson School of Management. It focuses on the fundamental and widely used exploratory data analysis technique of interactive visualization that is integral to modern business analytics. The key goal of this course is to prepare students for the rapidly changing digital environment faced by companies as it pertains to data-driven decisions. The students will also have hands?on experience with interactive data visualization using modern, state-of-the-art software on real-world datasets.

IDSC 4411 - Information Technology Governance and Assurance

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Information technology audit function, internal control, audit process, smart operations, network security, systems development life cycle, enterprise resource planning risk, compliance issues. IT governance, business continuity, frameworks/methodologies. Lectures, case studies, real-world examples. prereq: 3001

IDSC 4444 - Descriptive and Predictive Analytics

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Descriptive and Predictive Analytics exposes students to a number of data mining and machine learning methods, including: exploratory methods (such as association rules and cluster analysis), predictive methods (such as K-NN and decision trees), and text mining methods. The course combines theoretical lectures with lab lectures, where the methods are practically implemented using the software R. prereqs: IDSC 3001; non-MIS majors also need IDSC 4110

IE 5012 - Discrete Optimization Methods and Applications

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

Discrete and combinatorial optimization techniques; heuristics; dynamic programming; handling uncertainty in optimization models. Applications in logistics, healthcare, data analysis. (Previously offered as IE 3012.) prereq: (i) MATH 2374, MATH 2142 or MATH 2373 or equivalent, (ii) Upper Division CSE, (iii) CSCI 1133 or equivalent

IE 3013 - Optimization for Machine Learning

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

Machine learning has been widely used in areas such as computer vision, search engines, speech recognition, robotics, recommendation systems, bioinformatics, social networks, and finance. It has become an important tool in prediction and data analysis. This course introduces some fundamental solution methods for solving various optimization models arising in the context of machine learning.

IE 4894 - Directed 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 5513 - Engineering Safety

Credits:	4.0 [max 4.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Occupational, health, and product safety. Standards, laws, and regulations. Hazards and their engineering control, including general principles, tools and machines, mechanics and structures, electrical safety, materials handling, fire safety, and chemicals. Human behavior and safety, procedures and training, warnings and instructions. prereq: Upper div CSE or grad student

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.

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 5551 - Production and Inventory Systems

Credits:	4.0 [max 4.0]
Typically offered:	Every Spring

Inventory control, supply chain management, demand forecasting, capacity planning, aggregate production and material requirement planning, operations scheduling, and shop floor control. Quantitative models used to support decisions. Implications of emerging information technologies and of electronic commerce for supply chain management and factory operation. prereq: CNR or upper div or grad student

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:	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:	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

MATH 4653 - Elementary Probability

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall & Spring

Probability spaces, distributions of discrete/continuous random variables, conditioning. Basic theorems, calculational methodology. Examples of random sequences. Emphasizes problem-solving. prereq: [2263 or 2374 or 2573]; [2283 or 2574 or 3283] recommended

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]

MATH 5485 - Introduction to Numerical Methods I

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall

Solution of nonlinear equations in one variable. Interpolation, polynomial approximation. Methods for solving linear systems, eigenvalue problems, systems of nonlinear equations. prereq: [2243 or 2373 or 2573], familiarity with some programming language

MATH 5651 - Basic Theory of Probability and Statistics

Credits:	4.0 [max 4.0]
Course Equivalencies:	Math 5651/Stat 5101
Typically offered:	Every Fall & Spring

Logical development of probability, basic issues in statistics. Probability spaces, random variables, their distributions/expected values. Law of large numbers, central limit theorem, generating functions, sampling, sufficiency, estimation. prereq: [2263 or 2374 or 2573], [2243 or 2373]; [2283 or 2574 or 3283] recommended.

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:	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

This course is about the foundational principles of management, encompassing disciplinary and topical boundaries. We will look at these principles from the perspective of how they guide action, specifically: planning, organizing, leading and controlling. By the end of the course, students will know the basics of how to set up organizations to be effective and innovative, and not just efficient. During the course, you will engage with the material in the course and understand how management frameworks can be used to choose the right internal structures and processes that can best react to your particular industry context and general business environment.

MGMT 3015 - Introduction to Entrepreneurship

Credits:	4.0 [max 4.0]
Course Equivalencies:	IBUS 3010/MGMT 3010/MGMT 3015
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 3045 - Understanding the International Environment of Firms: International Business

Credits:	2.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Theories, frameworks, tools, and facts for understanding the environment of firms in international competition. Main world-level economic flows (trade, investment, finance). How country-/industry-level economic, political, and sociocultural factors influence behavior/functions of firms in international competition. prereq: MGMT 3001 or 3004

MGMT 4032 - Corporate Strategy

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Fall & Spring

This course examines issues of corporate strategy, i.e., issues associated with creating and managing a firm that operates in multiple businesses. Some of the key questions we shall seek to address through this course are: ? What are the drivers of corporate scope? How should a firm choose the activities/businesses it participates in? ? What are the sources of value for a firm from being diversified across multiple businesses? ? What are the challenges associated with managing across multiple businesses and markets? ? How are these challenges best dealt with? What structures and processes enable successful corporate diversification over time? The learning objective of this course is to help you learn to identify and define successful corporate strategies and offer solutions for the common problems that diversified firms face. The course not only introduces you to core concepts around corporate strategy, but it also seeks to develop your ability to critically evaluate the strategies of multi-business firms, through the extensive use of case discussions. prereq: Mgmt 3004

MGMT 4033 - Strategy Implementation

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

This course focuses on implementing and executing strategy at both the organizational and functional level. It will focus on the relationship between strategy formulation and execution, the systematic and structural problems with implementing strategy, and various methods to minimize these problems. The course is designed both as a standalone topic and to deepen the student?s understanding of the other strategic concepts covered in the strategy minor. prereq: Mgmt 3004 or 3001.

MGMT 4035 - Mergers & Acquisitions Strategy

Credits:	2.0 [max 2.0]
Grading Basis:	A-F only
Typically offered:	Every Spring

This course focuses on the strategic use of mergers and acquisitions (M&A) as a means of new market entry and growth. It covers such questions as: when should one pursue an acquisition? What are the sources of value from an acquisition? What are the common challenges acquirers face? What should acquirers look for in a potential target? How should they integrate a target post-acquisition? It also considers the sell-side strategies for firms looking to exit businesses through divestiture. The learning objective of this course is to help you learn to identify and define successful mergers and acquisitions, and offer solutions for the common problems that firms face when undertaking acquisitions. The course not only introduces you to core concepts around M&A, it also seeks to develop your ability to critically evaluate firms? M&A choices, and to effectively communicate your assessment of these choices to a business audience. prereq: Mgmt 4032

MGMT 4044 - Negotiation Strategies

Credits:	4.0 [max 4.0]
Grading Basis:	A-F only
Typically offered:	Every Fall

This course is an introduction to the theory and practice of negotiation as the art and science of securing agreements between two or more interdependent parties seeking to maximize their own outcomes. The concepts you learn and the skills you develop in this class will apply to both your work and personal negotiations. At the heart of this class is the idea that the best way to learn to negotiate is by engaging in negotiation and then rigorously analyzing your experience. Therefore, this course is designed to be a highly interactive learning experience. The role of the course instructor is to help you get the most out of this experience by selecting relevant and compelling exercises and readings, as well as by facilitating engaging and meaningful discussion of class negotiations, negotiation research and best practices.

MGMT 4055 - Managing Innovation and Change In Action

Credits:	2.0 [max 2.0]
Course Equivalencies:	IBus 4050/Mgmt 4055
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

This course focuses on how business organizations innovate and change. The course covers foundational topics and combines both theoretical insights and practical knowledge based on cases and hands-on exercises. The class topics address the following questions: � What are the sources, types and patterns of innovation? � What are the characteristics of an organization?s innovation ecosystem? � How do organizations compete and collaborate in innovation ecosystems? � What are some external forces shaping organizational innovations? � How do organizations adapt to these external forces? By the end of this course, students will: Learn the key principles of success and failure of innovation and change in business organizations across different products, services and geographies. Apply course concepts to real organizational cases, diagnose problems and recommend solutions. Use clear written, verbal and online communication skills. Collaborate to create novel solutions to tasks and problems. Demonstrate the use of a wide range of qualitative and quantitative sources to support conclusions and recommendations. prereq: MGMT 3001 or MGMT 3004 or MGMT 3010 or MGMT 3015

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

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 4173 - New Venture Financing & Seed Stage Investing

Credits:	2.0 -4.0 [max 4.0]
Grading Basis:	OPT No Aud
Typically offered:	Every Fall & Spring

This experiential course is offered to University undergraduate students interested in learning about new venture financing through the operation of an independent angel investment fund. It serves as an introduction to the subject matter, while providing a forum for the students to review investment opportunities, connect with members from the entrepreneurial and investor communities, and learn about startup fundraising through direct participation in the investment process. This course is being offered to complement a student-owned private venture capital fund in collaboration with individual accredited investors, which was initially formed in April of 2018. In addition to the ongoing management of the fund operations and reporting, the students will be responsible for ongoing capital raising. Final authority for all investment decisions rests with the students.

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]
Course Equivalencies:	Mktg 3001/Mktg 3001H
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 or ECON 1165

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 course, you'll find out just how innovative, strategic, and creative manufacturing is. The course is 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.

MM 4045 - The Product Life Cycle in a Regulated Industry

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

There's much to learn when it comes to designing, developing, manufacturing, and selling something, but this course skillfully covers it all while teaching how to successfully commercialize a product. Students will delve into real-world analysis of product regulation of any kind--from a box of cereal to a medical device. After this course, you?ll be able to a) improve efficiency in any part of a product's life cycle, b) develop soft skills needed to clearly communicate your ideas for improvement, and c) fully wrap your brain around human factors and customer requirements that must be considered before the product's development is complete. This material has endless applications in the workplace. prereq: None.

MM 4311 - Sustainable Lean Manufacturing: Eliminating the Waste

Credits:	3.0 [max 2.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Spring

One of the most important skills you can cultivate in manufacturing (or really any line of work) is the ability to clear away the clutter and streamline the process. Sustainable Lean Manufacturing teaches students three things: 1) wasted time, effort, and money exist in every process involving a product or service; 2) it?s possible to clearly see and identify where waste occurs; and 3) there?s a surefire set of tools and techniques to make a process less wasteful and more efficient. Bottom line: students leave this course viewing everyday life with a different perspective, knowing there?s always room for improvement in workflow. prereq: None

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.

PA 5711 - Science, Technology & Environmental Policy

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Interplay of science, technology, the environment, and society. Approaches from across the social sciences will cover how science and technology can create new environmental pressures as well as policy challenges in a range of spheres from climate change to systems of intellectual property and international development.

PA 5721 - Energy Systems and Policy

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Impact of energy production/consumption choices on environmental quality, sustainable development, and other economic/social goals. Emphasizes public policy choices for energy/environment, linkages between them.

PA 5722 - Economics of Environmental Policy

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Introduction to economic principles and methods as they apply to environmental issues such as climate change, biodiversity conservation, and water quality. Course will cover benefit-cost analysis, methods of environmental valuation, as well as critiques of market-based solutions to environmental challenges.

PA 5724 - Climate Change Policy

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Existing and proposed approaches to mitigate and adapt to climate change through policies that cross scales of governance (from local to global) and impact a wide range of sectors. Exploration of climate change policy from a variety of disciplinary approaches and perspectives, emphasizing economic logic, ethical principles, and institutional feasibility. How policy can be shaped in the face of a variety of competing interests to achieve commonly desired outcomes. Students develop a deep knowledge of climate change in particular countries through a team final project. prereq: Intro microecon (such as Econ 1101 or equiv)

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:	PDes 3711/PDes 5711
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. prereq: PDes 2772 OR Junior/Senior (any major) or permission from instructor

PUBH 3801 - Health Economics and Policy

Credits:	3.0 [max 3.0]
Course Equivalencies:	ApEc 3801/PubH 3801
Typically offered:	Every Spring

Economics of health care markets. Problems faced by consumers/health care services. Builds on principles of supply/demand for health, health care/insurance, and role of government. Theoretical/empirical models/applications. prereq: Course on microeconomics, course on basic statistics

PUBH 6542 - Management of Health Care Organizations

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Role of hospital in health services delivery. Relationships with other systems and the community. Emphasizes governance, medical staff, and role of administrator. Lectures, on-site visits to health services organizations. prereq: MHA student or permission of instructor

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 - Sustainable Supply Chain and Operations

Credits:	3.0 [max 3.0]
Grading Basis:	A-F or Aud
Typically offered:	Every Fall & Spring

Sustainable Supply Chain and Operations Management focuses on the design and management of transformation processes to provide products and services to create value for the people, planet, and firm prosperity. On the one hand, supply chain and operations management involves the integration of activities and processes, to facilitate the flows of materials, services, finances, and information to convert inputs into the firms? primary products and services. Operational issues include the design of products and processes, the procurement of raw materials, the control of inventories, the maintenance of quality, the planning of human resources and facilities, and the delivery of products or services, so that customer expectations and needs are met. Operations also have significant interactions with other functional areas of the firm (e.g., finance, marketing, strategy, and accounting). Therefore, understanding the role of the operations function and its impact on the competitiveness of the firm from both tactical and strategic aspects is an important part of any manager's training. This course will introduce students to the fundamental concepts, operations practices, and models in both manufacturing- and service-oriented firms. The course will cover both quantitative and qualitative methods.

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 & Spring

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

This course teaches the essential tools and tasks to design an efficient supply chain planning and control system, including ERP, integrated business planning, forecasting, inventory management, capacity/production/material planning, and scheduling. 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 Fall & Spring

Technologies and technological change within/between firms as opportunities for professional leadership. Selecting technologies, nurturing their adoption, and ensuring their exploitation. prereq: 3001

SSM 3301 - Global Water Resource Use and Sustainability (ENV)

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall & Spring

What is the value of clean water? Explore the many facets of water, earth's most abundant resource. Ponder the value water for you, society, a region or nation; the complexities of ownership and protection; the influence of culture and traditions; and potential impacts of climate change. Consider realistic and holistic solutions to water issues.

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 & Spring

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]
Typically offered:	Every Fall & 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), (MATH 2142 or CSCI 2033 or MATH 2373 or MATH 2243)

STAT 5102 - Theory of Statistics II

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall & 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 3032 or 3301 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 Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.

STAT 5303 - Designing Experiments

Credits:	4.0 [max 4.0]
Typically offered:	Every Fall, Spring & Summer

Analysis of variance. Multiple comparisons. Variance-stabilizing transformations. Contrasts. Construction/analysis of complete/incomplete block designs. Fractional factorial designs. Confounding split plots. Response surface design. prereq: 3022 or 3032 or 3301 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. pre-req: STAT 3032 or 3301 or 3022 or 4102 or 5021 or 5102 or instr consent Although not a formal prerequisite of this course, students are encouraged to have familiarity with linear algebra prior to enrolling. Please consult with a department advisor with questions.

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. prereq: STAT 3022 or 3032 or 3301 or 5302 or 4051 or 8051 or 5102 or 4102

STAT 5511 - Time Series Analysis

Credits:	3.0 [max 3.0]
Typically offered:	Every Fall

Characteristics of time series. Stationarity. Second-order descriptions, time-domain representation, ARIMA/GARCH models. Frequency domain representation. Univariate/multivariate time series analysis. Periodograms, non parametric spectral estimation. State-space models. prereq: STAT 4102 or STAT 5102

WRIT 3562W - Technical and Professional Writing (WI)

Credits:	4.0 [max 4.0]
Course Equivalencies:	Writ 3562V/Writ 3562W
Grading Basis:	A-F only
Typically offered:	Every Fall, Spring & Summer

This course introduces students to technical and professional writing through various readings and assignments in which students analyze and create texts that work to communicate complex information, solve problems, and complete tasks. Students gain knowledge of workplace genres as well as to develop skills in composing such genres. This course allows students to practice rhetorically analyzing writing situations and composing genres such as memos, proposals, instructions, research reports, and presentations. Students work in teams to develop collaborative content and to compose in a variety of modes including text, graphics, video, audio, and digital. Students also conduct both primary and secondary research and practice usability testing. The course emphasizes creating documents that are goal-driven and appropriate for a specific context and audience.

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 Please note this course generally does not count in the Statistical Practice BA or Statistical Science BS degrees. Please consult with a department advisor with questions.

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 - Machine Learning Fundamentals

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, and knowledge of partial derivatives

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

University Catalogs

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