The mathematical concepts highlighted in this course include filtering, prediction, classification, decision-making, Markov chains, LTI systems, spectral analysis, and frameworks for learning from data. It also discusses applications to queueing theory, risk analysis and reliability theory. Quantitative models for operational and tactical decision making in production systems, including production planning, inventory control, forecasting, and scheduling. Group studies of selected topics. The IEOR department plans to offer the following courses in the Spring 2022 semester. Course Objectives: Insure students become familiar with the fundamental similarities and differences among simulation software packages. In this graduate course, we focus on the systematic design of databases and interfaces for commercial and industrial applications. Alternate formulations for integer optimization: strength of Linear Programming relaxations. Application of systems analysis and industrial engineering to the analysis, planning, and/or design of industrial, service, and government systems. Terms offered: Spring 2019, Spring 2017 Terms offered: Spring 2019, Fall 2015, Spring 2015, Supervised Independent Study and Research. Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). Fundamentals of Revenue Management: Read More [+], Prerequisites: IndEng 162, IndEng 169 and either IndEng 173 Or IndEng 172 (or equivalent introductory courses in mathematical programming and probability). The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). To train students in how to actually apply each method that is discussed in class, through a series of labs and programming exercises.5. Random walks and the GI/G/l queues. One of the grand challenges of this century is the modernization of electrical power networks. Grading/Final exam status: The grading option will be decided by the instructor when the class is offered. Supervised Independent Study and Research: Terms offered: Fall 2022, Fall 2021, Fall 2020, Applied Data Science with Venture Applications, Terms offered: Spring 2023, Spring 2022, Fall 2021. , LTI systems, spectral analysis, and frameworks for learning from data. descriptive, predictive, and prescriptive analytics. Individual study and research for at least one academic year on a special problem approved by a member of the faculty; preparation of the thesis on broader aspects of this work. Branch and Bound; Cutting plane methods; polyhedral theory. Introduction to Stochastic Processes: Read More [+]. develop custom Python scripts and functions to perform analytic computations; Applied Stochastic Process I: Read More [+], Prerequisites: Industrial Engineering 172,orStatistics134orStatistics200A. Introduction to Machine Learning and Data Analytics: Terms offered: Fall 2020, Fall 2019, Fall 2018, Logistics Network Design and Supply Chain Management, Terms offered: Spring 2022, Fall 2021, Spring 2021. for logistics will be considered through discussions and cases. , and semi-martingales. On the other hand, the Master of Analytics focuses on . Individual study for the comprehensive in consultation with the field adviser. https://ieor.berkeley.edu/wp-content/uploads/2021/10/iise_EDIT_2_captions.mp4, Meet One of UC Berkeleys Oldest Living Alumni, Dr. Ernst S. Valfer, Javad Lavaei Named AAIA Fellow and Awarded IEEE CSS Antonio Ruberti Young Researcher Prize, Berkeley IEOR Graduate Named to Forbes 30-Under-30 List, Student Stories: Community by Shreejal Luitel, B.A. Supervised Group Study and Research: Read Less [-], Terms offered: Prior to 2007 Approximations of combinatorial optimization problems, of stochastic programming problems, of robust optimization problems (i.e., with optimization problems with unknown but bounded data), of optimal control problems. Terms offered: Fall 2010, Fall 2008, Spring 2008, Terms offered: Fall 2010, Spring 2008, Fall 2007, Berkeley Berkeley Academic Guide: Academic Guide 2023-24. Individual Study for Doctoral Students: Read More [+], Individual Study for Doctoral Students: Read Less [-]. A deficient grade in INDENG172 may be removed by taking STAT 140. business/industry challenges using Python packages such as Pandas, NumPy, Matplotlib, scikit- Methods for evaluating real options will be presented. Applications will be given in such areas as reliability theory, risk theory, inventory theory, financial models, and computer science, among others. Convex Optimization and Approximation: Read More [+], Prerequisites: 227A or consent of instructor, Convex Optimization and Approximation: Read Less [-], Terms offered: Spring 2023 Individual Study for Master's Students: Read More [+], Fall and/or spring: 15 weeks - 0 hours of independent study per week, Summer: 8 weeks - 6-68 hours of independent study per week, Subject/Course Level: Industrial Engin and Oper Research/Graduate examination preparation, Individual Study for Master's Students: Read Less [-], Terms offered: Fall 2010, Spring 2008, Fall 2007 Students undertake intensive study of actual business situations through rigorous case-study analysis. Repeat rules: Course may be repeated for credit without restriction. Grading/Final exam status: Letter grade. The course introduces modern open source, computer programming tools, libraries, and code samples that can be used to implement data applications. Course Objectives: Students will understand the similarities and differences in methods for simulating the dynamics of complex, stochastic systems and apply these to model real systems. They will also learn about the interaction between operation and electricity market. Help us reach our goal Simulation for Enterprise-Scale Systems: Read More [+]. Courses Industrial Engineering and Operations Research (IND ENG) Industrial Engineering and Operations Research (IND ENG) Courses Expand all course descriptions [+] IND ENG 24 Freshman Seminars 1 Unit [+] IND ENG 66 A Bivariate Introduction to IE and OR 3 Units [+] IND ENG 98 Supervised Group Study and Research 1 - 3 Units [+] Fall and/or spring: 15 weeks - 2 hours of lecture and 2 hours of discussion per week, Introduction to Stochastic Processes: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 The course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. Through these examples, exercises in R, and a comprehensive team project, students will gain experience understanding and applying techniques such as linear regression, logistic regression, classification and regression trees, random forests, boosting, text mining, data cleaning and manipulation, data visualization, network analysis, time series modeling, clustering, principal component analysis, regularization, and large-scale learning. BerkeleyX offers interactive online classes and MOOCs from the worlds best universities. Monte Carlo simulations are used in a weekly laboratory to model systems that may be too complex to approximate accurately with deterministic, stationary, or static models; and to measure the robustness of predictions and manage risks in decisions based on data-driven models. Learn more about our facultys research, student activities, alumni game-changers, and how Berkeley IEOR is designing a more efficient world. Semi-Markov processes with emphasis on application. Integer Programming and Combinatorial Optimization: Read More [+], Integer Programming and Combinatorial Optimization: Read Less [-], Terms offered: Fall 2015, Fall 2014 Three hours of lecture per week. understand the array of mathematical toolkits provided by the Python packages covered. The course will focus on two-dimensional, i.e., bivariate, examples where the problems and methods are amenable to visualization and geometric intuition. a series of design problems individually and in teams. Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. Final exam not required. You will learn techniques to accelerate product success and avoid common mistakes. The far-reaching research done at Berkeley IEOR has applications in many fields such as energy systems, healthcare, sustainability, innovation, robotics, advanced manufacturing, finance, computer science, data science, and other service systems. Healthcare Analytics: Read More [+], Prerequisites: Courses in mathematical modeling (such as INDENG160 and INDENG172) and computer programming (such as CS C8 or CS 61A) are recommended. data sets. Engineering Statistics, Quality Control, and Forecasting: Read More [+], Prerequisites: INDENG172, or STAT134, or an equivalent course in probability theory. Seminar on selected topics from financial and technological risk theory, such as risk modeling, attitudes towards risk and utility theory, portfolio management, gambling and speculation, insurance and other risk-sharing arrangements, stochastic models of risk generation and run off, risk reserves, Bayesian forecasting and credibility approximations, influence diagrams, decision trees. Review of linear and nonlinear optimization models, including optimization problems with discrete decision variables. Course topics include an introduction to polyhedral theory, cutting plane methods, relaxation, decomposition and heuristic approaches for large-scale optimization problems. Control and Optimization for Power Systems: Read More [+]. Sample topics include, but are not limited to, resource allocation and pricing under uncertain sequential demand, mechanism design, discrete choice models, static and dynamic assortment optimization, real-time recommendations, spatial supply response and supply re-balancing in bike/ride sharing systems. All courses are subject to change. . Undergraduate Field Research in Industrial Engineering: Directed Group Studies for Advanced Undergraduates. This will be an introductory first-year graduate course covering fundamental models in production planning and logistics. Fall and/or spring: 15 weeks - 1 hour of seminar per week, Subject/Course Level: Industrial Engin and Oper Research/Undergraduate. One or more systems, which may be public or in the private sector, will be selected for detailed analysis and re-designed by student groups. Supervised independent study for lower division students. Analysis and Design of Databases: Read More [+], Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week, Analysis and Design of Databases: Read Less [-], Terms offered: Spring 2017, Spring 2016, Spring 2015 Alternative to final exam. Terms offered: Spring 2018, Fall 2016, Spring 2016 Programming material includes the theory behind random variable generation for a variety of common variables. This course will introduce graduate and upper division undergraduate students to modern methods for simulating discrete event models of complex stochastic systems. This seminar and discussion class aims to survey current and classic research on innovation and help Cases in Global Innovation: Read More [+], Fall and/or spring: 8 weeks - 2 hours of lecture per week, Cases in Global Innovation: Read Less [-], Terms offered: Prior to 2007 , courses, technical electives, or otherwise ) models, including optimization problems plans. A More efficient world class, through a series of labs and programming exercises.5 queueing theory, analysis. Avoid common mistakes, Subject/Course Level: industrial Engin and Oper Research/Undergraduate of Analytics focuses on systems... Packages covered and how Berkeley IEOR is designing a More efficient world alumni... That is discussed in class, through a series of design problems individually and in.! A series of design problems individually and in teams Master of Analytics focuses.. Of databases and interfaces for commercial and industrial applications and geometric intuition course, we focus two-dimensional. 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