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Survey of solution techniques and problems that have formulations in terms of flows in networks. Copyright 2023-24, UC Regents; all rights reserved. Discussion, practice, and review of fundamentals, issues, and best practices in teaching for any engineering course. Instructors Type Term Exam Solution Flag (E) Flag (S) Munoz Designed for students from any science/engineering major, this upper-division course will introduce students to optimization models, and train them to use software tools to model and solve optimization problems. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. At Berkeley IEOR, we expand the frontiers of optimization, stochastics and data science enabling transformative decision analytics and technologies to solve grand challenges in transportation, supply chains, healthcare, energy, robotics, finance and risk management. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. Summer: 6 weeks - 2.5-10 hours of independent study per week8 weeks - 2-7.5 hours of independent study per week10 weeks - 1.5-6 hours of independent study per week, Supervised Independent Study: Read Less [-], Terms offered: Prior to 2007 This course will cover topics related to healthcare analytics, including: optimizing chronic disease management, designing matching markets for health systems, developing predictive analytics models, and managing resource utilization. Final exam not required. On the other hand, the Master of Analytics focuses on . IEOR leverages computing to better manage the massive amounts of information available today. The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. Elective course that provides a systematic evaluation of decision-making problems under uncertainty. Course Objectives: Students will learn how to model random phenomena and learn about a variety of areas where it is important to estimate the likelihood of uncertain events. This course is designed primarily for upper-level undergraduate and graduate students interested in examining the major challenges and success factors entrepreneurs and innovators face in globalizing a company, product, or service. models characteristic of each subfield. This course is geared towards understanding operational, strategic, and tactical aspects of supply chain man agement. Students will solve a series of design problems individually and in teams. This seminar and discussion class aims to survey current and classic research on innovation and help 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. Industrial Engineering and Operations Research (IEOR) Dept University of California at Berkeley Lectures and Labs: MW 5-6:30, 3106 Etcheverry Hall Web Page: www.ieor.berkeley.edu/~ieor170 3 Credits. Applications in Data Analysis: Read Less [-], Terms offered: Spring 2023, Spring 2022 Risk Modeling, Simulation, and Data Analysis: Supply Chain Innovation, Strategy, and Analytics. optimization methods using software packages, and will require some programming. Recommended, but not required to be taken after or along with Engineering 198, Fall and/or spring: 15 weeks - 2 hours of lecture per week, Cases in Global Innovation: China: Read Less [-], Terms offered: Prior to 2007 Applied Data Science with Venture Applications: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 They will also manage hypothetical portfolios throughout the course. Python for Analytics: Read More [+]. Course Objectives: Undergraduate Field Research in Industrial Engineering: Directed Group Studies for Advanced Undergraduates. Production Systems Analysis: Read More [+], Prerequisites: INDENG160, INDENG173, INDENG162, INDENG165, and ENGIN120, Production Systems Analysis: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 a series of design problems individually and in teams. The emphasis will be on computational methods such as variants of GARCH, Black-Litterman, conic optimization, Monte Carlo simulation for risk and optimization, factor modeling. Facilities Design and Logistics: Read More [+], Prerequisites: 262A, and either 172 or Statistics 134, Facilities Design and Logistics: Read Less [-], Terms offered: Spring 2021, Spring 2014, Spring 2013 Students work on a field project under the supervision of a faculty member. Theory of optimization for constrained and unconstrained problems. It also discusses applications to queueing theory, risk analysis and reliability theory. This course introduces you to the field of supply chain management through a series of lectures and case studies that emphasize innovative concepts in supply chain management that have proven to be beneficial for a good number of adopters. Introduce students to modern techniques for developing computer simulations of stochastic discrete-event models and experimenting with such models to better design and operate dynamic systems. Terms offered: Spring 2023, Spring 2022, Fall 2020, Probability and Risk Analysis for Engineers. BerkeleyX offers interactive online classes and MOOCs from the worlds best universities. Course topics include an introduction to polyhedral theory, cutting plane methods, relaxation, decomposition and heuristic approaches for large-scale optimization problems. Review of linear and nonlinear optimization models, including optimization problems with discrete decision variables. GSI Ahmad Masad 16amasad[at]berkeley.edu Please include [IEOR 130] at the beginning of your subject, e.g. understand the array of mathematical toolkits provided by the Python packages covered. Portfolio and Risk Analytics: Read More [+], Prerequisites: A basic understanding of statistics and optimization, as well as fluency in a programming, language is required, Portfolio and Risk Analytics: Read Less [-], Terms offered: Prior to 2007 Courses. The second part of the course will discuss the formulation and numerical implementation of learning-based model predictive control (LBMPC), which is a method for robust adaptive optimization that can use machine learning to provide the adaptation. The course introduces modern open source, computer programming tools, libraries, and code samples that can be used to implement data applications. The course is intended for graduate students at the Masters level looking for a concrete introduction Terms offered: Spring 2023, Spring 2022, Spring 2021, Spring 2020. , and predictive models characteristic of each subfield. Freshman Seminars: Read More [+]. Industrial Engineering and Operations Research 173. The course will discuss applications such as dieting, scheduling, and transportation. Students undertake intensive study of actual business situations through rigorous case-study analysis. Individual study for the comprehensive in consultation with the field adviser. This course addresses modeling and algorithms for integer programming problems, which are constrained optimization problems with integer-valued variables. written paper is also required. Dynamic Production Theory and Planning Models: Terms offered: Spring 2017, Spring 2014, Spring 2011, Terms offered: Spring 2016, Spring 2015, Spring 2014, Group Studies, Seminars, or Group Research. Student Learning Outcomes: LEARNING GOALS Systems Analysis and Design Project: Read More [+], Systems Analysis and Design Project: Read Less [-], Terms offered: Prior to 2007 In addition, qualitative issues in distribution network structuring, centralized versus decentralized network control, variability in the supply chain, strategic partnerships, and product design for logistics will be considered through discussions and cases. Berkeley Seminars are offered in all campus departments, and topics vary from department to department and semester to semester. Recommended but not required to be taken after or along with Engineering 198, Cases in Global Innovation: South Asia: Read Less [-], Terms offered: Fall 2022 Control and Optimization for Power Systems: Read More [+]. Credit Restrictions: Students will receive no credit for INDENG172 after completing STAT134, or STAT 140. Our researchers create new fields of optimization and push the boundaries in convex and non-convex optimization, integer and combinatorial optimization to find solutions to grand challanges with massive data sets. Convex optimization as a systematic approximation tool for hard decision problems. Group Studies, Seminars, or Group Research: Read More [+], Fall and/or spring: 15 weeks - 1-4 hours of colloquium per week. 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. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. To train students in how to actually apply each method that is discussed in class, through a series of labs and programming exercises.5. For students to gain some project-based practical data science experience, which involves identifying a relevant problem to be solved or question to be answered, gathering and cleaning data, and applying analytical techniques.6. Over the duration of this course, students will examine case studies of foreign companies seeking to start a new venture, introduce a new product or service to the South Asian market, or South Asian companies seeking to adapt a U.S or western business model. Queueing Theory: Read More [+], Terms offered: Fall 2021, Spring 2018, Spring 2017 Help us reach our goal Note: the course is a mixture of modeling art, analytical science, and computational technology. use Python and core scienti Enrollment restrictions apply. All courses are subject to change. Prerequisites: Students should have a solid knowledge of calculus, including multiple variable integration, such as MATH1A and MATH1B or MATH16A and MATH16B, as well as programming experience in Matlab or Python. Credit Restrictions: Course restricted to Freshman students. Emphasis will be placed on both the use of computers and the theoretical analysis of models and algorithms. Conditional Expectation. Semi-Markov processes with emphasis on application. to adapt a U.S. or western business model to the China market. The focus is on converting the theory of optimization into effective computational techniques. Alternative to final exam. Methods for evaluating real options will be presented. At Berkeley IEOR, we expand the frontiers of optimization, stochastics and data science enabling transformative decision analytics and technologies to solve grand challenges in transportation, supply chains, healthcare, energy, robotics, finance and risk management. We recently sat down with MoonSoo Choi to discuss his time as an undergraduate student and his current role as Senior Manager of Data Science at Walmart. With more than 4,000 alumni, 20 faculty, 20 advisory board members and 400 students, the IEOR department is a rapidly growing community equipped with tools and resources to make a large impact in industry, academia, and society. Study of algorithms for non-linear optimization with emphasis on design considerations and performance evaluation. It then covers rigorously and in depth the most fundamental probability concepts for financial engineers, including stochastic integral, stochastic differential equations, and semi-martingales. A deficient grade in INDENG172 may be removed by taking STAT 140. Minimum cost flows. Please use this as a guide for planning purposes. About a third of the course will be devoted to system modeling, with the remaining two-thirds concentrating on simulation experimental design and analysis. This is a Masters of Engineering course, in which students will develop a fundamental understanding of how randomness and uncertainty are root causes of risk in modern enterprises. Students will gain experience with a commercial database management system and will work in teams with Readings are drawn from economics, organizations, South Asian companies seeking to adapt a U.S or western business model. The last part of the course will deal with inverse decision-making problems, which are problems where an agent's decisions are observed and used to infer properties about the agent. The course is intended for graduate students at the Masters level looking for a concrete introduction, Introduction to Data Modeling, Statistics, and System Simulation, Terms offered: Spring 2023, Spring 2017, Spring 2015. Explore the Arts Research Center at UC Berkeley a think tank for the arts and a genuinely interdisciplinary space. Applied Data Science with Venture Applications: Introduction to Machine Learning and Data Analytics, Terms offered: Spring 2023, Fall 2022, Spring 2022. 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. Supervised independent study for lower division students. Berkeley, CA 94720-1702 (510) 642-7594 [email protected] Hours: Monday - Thursday, 8 a.m.-5 p.m. Friday, 10 a.m.-5 p.m. 4141 Etcheverry Hall #1777 (510) 642-5484 ieor.berkeley.edu Degree worksheets: 2013 | 2014 | 2015 | 2016 | 2017 | 2018 Previous Undergraduate Programs: 2013 | 2014 | 2015 | 2016 | 2017 Probability and Risk Analysis for Engineers: Read More [+]. Logistics Network Design and Supply Chain Management: Read More [+], Prerequisites: INDENG160, INDENG162 or senior standing, Logistics Network Design and Supply Chain Management: Read Less [-], Terms offered: Not yet offered Formerly Engineering 120. The first part of the course will cover statistical modeling procedures that can be defined as the minimizer of a suitable optimization problem. the instructor in order to solidify the lectures into practical experience using Python for analytics. The main goal is to develop proficiency in common optimization modeling languages, and learn how to integrate them with underlying optimization solvers. Algorithms for integer optimization problems. Deadline Friday, January 6, 2023, 8:59 pm PST FAQ Concentrations Management Science & Engineering FinTech Introduction to Production Planning and Logistics Models: Terms offered: Fall 2012, Spring 2005, Spring 2004, Terms offered: Spring 2021, Spring 2014, Spring 2013. competition, revenue management in queueing systems, information intermediaries, and health care. The course is focused around intensive study of actual business situations through rigorous case-study analysis. IEOR leverages computing to better manage the massive amounts of information available today. doctoral students formulate their research designs. understanding of supply chain management. Course Objectives: Students will learn how to model random phenomena that evolves over time, as well as the simulation techniques that enable the replication of such problems using a computer. New issues raised by the World Wide Web. Industrial Engineering and Operations Research (IND ENG), Terms offered: Fall 2017, Fall 2016, Fall 2015. applications such as dieting, scheduling, and transportation. Convex Optimization and Approximation: Read More [+], Prerequisites: 227A or consent of instructor, Convex Optimization and Approximation: Read Less [-], Terms offered: Spring 2023 This course is designed primarily for upper-level undergraduate and graduate students interested in examining the major challenges and success factors entrepreneurs and innovators face in globalizing a company product or service, with a focus on China. Course Objectives: Provide an introduction to the field of Industrial Engineering and Operations Research through a series of lectures. Terms offered: Spring 2014, Fall 2011, Fall 2009. design, discrete choice models, static and dynamic assortment optimization, real-time recommendations, spatial supply response and supply re-balancing in bike/ride sharing systems. 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