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. develop custom Python scripts and functions to perform analytic computations; 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 Spring 2017: IEOR 258 - Control and Optimization for Power Systems. Describe different mathematical abstractions used in IEOR (e.g., graphs, queues, Markov chains), and how to use these abstractions to model real-world problems. Advanced topics in information management, focusing on design of relational databases, querying, and normalization. Linear Programming and Network Flows: Read More [+], Linear Programming and Network Flows: Read Less [-], Terms offered: Spring 2023 Students will be exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses. Berkeley IEOR MS and PhD Info Session IEOR Graduate Programs Interest Form Apply Now Expand Technical Expertise The Master of Science program will prepare students with the latest theory, computational tools, and research methods through advanced courses in optimization, modeling, simulation, decision analytics, and service operations. Analytical techniques for the improvement of manufacturing performance along the dimensions of productivity, quality, customer service, and throughput. Financial Engineering Systems I: Read More [+], Prerequisites: 221 or equivalent; 172 or Statistics 134 or a one-semester probability course, Financial Engineering Systems I: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Student teams implement an enterprise-scale simulation in a semester-length design project. Topics include the firm's key operations, strategic issues, and managerial leadership including personal leadership and talent management. Survey of solution techniques and problems that have formulations in terms of flows in networks. descriptive, predictive, and prescriptive analytics. It then covers Brownian motion, martingales, and Ito's calculus, and deals with risk-neutral pricing in continuous time models. Advanced graduate course for Ph.D. students interested in pursuing a professional/research career in financial engineering. Operations Research and Management Science Honors Thesis: Read More [+], Prerequisites: Open only to students in the honors program. 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. Nonlinear and Discrete Optimization: Read More [+], Nonlinear and Discrete Optimization: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Grading: Offered for satisfactory/unsatisfactory grade only. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. Algorithms for selected network flow problems. Instructor Professor Robert C. Leachman 510-517-6113 leachman[at]ieor.berkeley.edu Office hours: MWF 11:00-12:00pm Online via Zoom . Each math concept is linked to implementation using Python using libraries for math array functions (NumPy), manipulation of tables (Pandas), long term storage (SQL, JSON, CSV files), natural language (NLTK), and ML frameworks. doctoral students formulate their research designs. Models, algorithms, and analytical techniques for inventory control, production scheduling, production planning, facility location and logistics network design, vehicle routing, and demand forecasting will be discussed. Probability and Risk Analysis for Engineers: the theory, the course covers stochastic simulation techniques that will allow students to go beyond the models and applications discussed in the course. Terms offered: Spring 2018, Fall 2016, Spring 2016 Help us reach our goal Simulation for Enterprise-Scale Systems: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 exploratory analytics to systems analytics in an industry context, including communication of Specialized strategies by integer programming solvers. Economics of Supply Chains: Read More [+], Prerequisites: Basics Optimization and Probability (IndEng 240, IndEng 241, or equivalent), Economics of Supply Chains: Read Less [-], Terms offered: Spring 2023, Spring 2017, Spring 2015 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 Terms offered: Fall 2017, Fall 2016, Fall 2015 The course includes laboratory assignments, which consist of hands-on experience. Engineering Statistics, Quality Control, and Forecasting: Read More [+], Prerequisites: INDENG172, or STAT134, or an equivalent course in probability theory. The IEOR department is excited to announce that more than 50% of our Fall 2022 undergraduate and master's cohorts are female-identifying and non-binary. Fall and/or spring: 15 weeks - 3 hours of lecture per week. Grading/Final exam status: Letter grade. Includes formulation of risk problems and probabilistic risk assessments. Summer: 6 weeks - 7.5 hours of lecture and 2.5 hours of discussion per week, Engineering Statistics, Quality Control, and Forecasting: Read Less [-], Terms offered: Spring 2022, Spring 2021, Fall 2019 This course will study and draw connections between disparate fields to trace the development and influence of this view. Instructors Type Term Exam Solution Flag (E) Flag (S) Shanthikumar 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. Markovian queues; product form results. This course is concerned with improving processes and designing facilities for service businesses such as banks, health care organizations, telephone call centers, restaurants, and transportation providers. Credit Restrictions: Enrollment is restricted; see the Introduction to Courses and Curricula section of this catalog. 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. Note: the course is a mixture of modeling art, analytical science, and computational technology. Industrial Engineering and Operations Research (IEOR) Dept University of California at Berkeley Lecture: MW 12-1, 3113 Etcheverry Hall, Lab: F 2-4, 1173 Etcheverry This course explores how databases are designed, implemented, used and maintained, with an emphasis on industrial and commercial 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. Sensitivity analysis, parametric programming, convergence (theoretical and practical). 30% Notebook with Lecture Notes. Spring 2018: IEOR 262B - Mathematical Programming II. The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. Individual investigation of advanced industrial engineering problems. All courses are subject to change. Major topics in the course include design of service processes, layout and location of service facilities, demand forecasting, demand management, employee scheduling, service quality management, and capacity planning. Students develop research designs and present each week and formally for their final. Homeworks and Lab Quizzes: Hardcopies will be . With the growing complexity of providing healthcare, it is increasingly important to design and manage health systems using engineering and analytics perspectives. Applied Dynamic Programming: Read More [+], Applied Dynamic Programming: Read Less [-], Terms offered: Spring 2020, Spring 2010, Spring 2009 Advanced Topics in Industrial Engineering and Operations Research, Terms offered: Spring 2018, Fall 2016, Spring 2016. Industrial Engineering and Operations Research 162 . Algorithms for integer optimization problems. be used to fulfill any engineering unit or elective requirements. understand the array of mathematical toolkits provided by the Python packages covered. Teach strengths and weaknesses of different approaches for a foundation for selecting methodologies. IEOR is the process of inventing and designing ways to analyze and improve complex systems. Introduce the different technologies used to develop simulation models and simulator products in order to become critical consumers of simulation study results. Quality estimates of the resulting approximation. Industrial Engineering and Operations Research 173. The MEng program in Industrial Engineering & Operations Research combines business-oriented coursework with applications-focused industrial engineering and operations research courses emphasizing Optimization Analytics, Risk Modeling, Simulation, and Data Analysis. designed to prepare students for the applied analytics problems and projects they will encounter in Students will be exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses. Advanced Mathematical Programming: Read More [+], Advanced Mathematical Programming: Read Less [-], Terms offered: Spring 2016, Spring 2015, Spring 2014 Minimum-cost life and replacement analysis. Theory of optimization for constrained and unconstrained problems. Convex Optimization and Approximation: Read More [+], Prerequisites: 227A or consent of instructor, Convex Optimization and Approximation: Read Less [-], Terms offered: Spring 2023 Embedded Markov chains. GSI Ahmad Masad 16amasad[at]berkeley.edu Please include [IEOR 130] at the beginning of your subject, e.g. PASTA. 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. This course introduces students to key techniques in machine learning and data analytics through a diverse set of examples using real datasets from domains such as e-commerce, healthcare, social media, sports, the Internet, and more. Course topics include an introduction to polyhedral theory, cutting plane methods, relaxation, decomposition and heuristic approaches for large-scale optimization problems. Supply Chain Operation and Management: Read More [+], Supply Chain Operation and Management: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021, Spring 2020 Please use this as a guide for planning purposes. Students taking Ind Eng 242 cannot receive credit for Ind Eng 142. The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). This course will not require pre-requisites and will present the core concepts in a self-contained manner that is accessible to Freshmen to provide the foundation for future coursework. WWW design and queries. Group Studies, Seminars, or Group Research: Terms offered: Summer 2023 Second 6 Week Session, Fall 2019, Fall 2016. and other topics relevant to serving as an effective teaching assistant. Final exam required. Basic first year graduate course in optimization of non-linear programs. Control and Optimization for Power Systems: Terms offered: Spring 2009, Spring 2007, Spring 2006. use machine learning to provide the adaptation. Individual Study or Research: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Prerequisites: IEOR 240 Optimization Analytics, IEOR 241 Risk Modeling & Simulation Analytics, IEOR 242 Applications in Data Analysis. Credit Restrictions: Students will receive no credit for Ind Eng 171 after taking UGBA105. Models on production/inventory planning, logistics, portfolio optimization, factor modeling, classification with support vector machines. Random walks and the GI/G/l queues. Through a series of real-world examples, students will learn to identify opportunities to leverage the capabilities of data analytics and will see how data analytics can provide a competitive edge for companies.4. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Introduction to Martinjales. Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of discussion per week, Summer: 8 weeks - 4 hours of lecture and 2 hours of discussion per week, Principles of Engineering Economics: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Applied Data Science with Venture Applications: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 The course introduces modern open source, computer programming tools, libraries, and code samples that can be used to implement data applications. The technical material will be presented in the context of engineering team system design and operations decisions. Innovations that we will discuss include collaborative forecasting, social media, online procurement, and technologies such as RFID. Economics and Dynamics of Production: Read More [+], Prerequisites: 262A (may be taken concurrently), Mathematics 104 recommended, Economics and Dynamics of Production: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Industrial Design and Human Factors: Read More [+], Industrial Design and Human Factors: Read Less [-], Terms offered: Spring 2023, Spring 2022, Fall 2020 The Master of Engineering program in Industrial Engineering & Operations Research is a one year full-time program that combines business-oriented coursework with applications-focused industrial engineering and operations research courses emphasizing Optimization Analytics, Risk Modeling, Simulation, and Data Analysis. models characteristic of each subfield. It is applied to a broad range of applications from manufacturing to transporation to healthcare. A course on financial concepts useful for engineers that will cover, among other topics, those of interest rates, present values, arbitrage, geometric Brownian motion, options pricing, & portfolio optimization. Students work in teams with local companies on a database design project. Enrollment restrictions apply. Terms offered: Spring 2019, Spring 2017 Design of such systems requires familiarity with human factors and ergonomics, including the physics and perception of color, sound, and touch, as well as familiarity with case studies and contemporary practices in interface design and usability testing. Course does not satisfy unit or residence requirements for bachelor's degree. Some programming experience/literacy is expected, Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week, Introduction to Machine Learning and Data Analytics: Read Less [-], Terms offered: Fall 2022 Industrial and Commercial Data Systems: Read More [+], Fall and/or spring: 15 weeks - 2 hours of lecture and 2 hours of laboratory per week, Industrial and Commercial Data Systems: Read Less [-], Terms offered: Spring 2023 Prior exposure to optimization is helpful but not strictly necessary. Study of algorithms for non-linear optimization with emphasis on design considerations and performance evaluation. Graph and network problems as linear programs with integer solutions. New issues raised by the World Wide Web. The second half of the course will discuss the most recent topics in financial engineering, such as credit risk and analysis, risk measures and portfolio optimization, and liquidity risk and models. 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 Enable the students to recognize when problems can be modeled as integer optimization problems. 4189 Etcheverry Hall. Students will work primarily on modeling exercises, which will develop confidence in modeling and solve optimization methods using software packages, and will require some programming. optimization methods using software packages, and will require some programming. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation. Experimenting with Simulated Systems: Read More [+], Prerequisites: 165 or equivalent statistics course, and some computer programming background, Instructors: Ross, Schruben, Shanthikumar, Experimenting with Simulated Systems: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Prerequisites: upper division standing. Learn more. Elective course that provides a systematic evaluation of decision-making problems under uncertainty. The focus is on converting the theory of optimization into effective computational techniques. Terms offered: Spring 2022, Spring 2016, Spring 2015, Terms offered: Fall 2021, Spring 2018, Spring 2017, Integer Programming and Combinatorial Optimization, Terms offered: Spring 2020, Spring 2010, Spring 2009. Repeat rules: Course may be repeated for credit when topic changes. The course is focused first on developing an open-ended-real world project relating to data science. Prerequisites: 262A, 263A or equivalents and some programming experience, Introduction to Data Modeling, Statistics, and System Simulation: Read Less [-], Terms offered: Spring 2023, Spring 2022, Fall 2021 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. This undergraduate course will focus on fundamental models and algorithms for RM. Integer Programming and Combinatorial Optimization: Read More [+], Integer Programming and Combinatorial Optimization: Read Less [-], Terms offered: Fall 2015, Fall 2014 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. 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. This will be an introductory first-year graduate course covering fundamental models in production planning and logistics. IEOR 130; IEOR 142; IEOR 150; IEOR 151; IEOR 153; IEOR 160; IEOR 161; IEOR 162 The reversed chain concept in continuous time Markov chains with applications of queueing theory. Individual study for the comprehensive in consultation with the field adviser. Spring 2018: IEOR 268 - Applied Dynamic Programming. Share an intellectual experience with faculty and students by reading "Interior Chinatown" over the summer, attending author Charles Yu's live event on August 26, signing up for L&S 10: The On the Same Page Course, and participating in fall program activities. Familiarity with algorithm design and mathematical maturity recommended, Fundamentals of Revenue Management: Read Less [-], Terms offered: Fall 2020, Fall 2019, Fall 2018 The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. 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. 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. The Berkeley Seminar Program has been designed to provide new students with the opportunity to explore an intellectual topic with a faculty member in a small-seminar setting. . Simulation for Enterprise-Scale Systems: Read More [+]. On the other hand, the Master of Analytics focuses on . Decision Analytics: Read More [+], Terms offered: Spring 2022, Spring 2021, Fall 2020 The course content exposes students interested in internationally oriented careers to the strategic thinking involved in international engagement and expansion. Systems Analysis and Design Project: Read More [+], Systems Analysis and Design Project: Read Less [-], Terms offered: Prior to 2007 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 Course Objectives: 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. Elective requirements comprehensive in consultation with the field adviser: MWF 11:00-12:00pm Online via Zoom actual... Teams with local companies on a database design project social media, Online procurement and!: 15 weeks - 3 hours of lecture per week technical electives, or otherwise ) Master of analytics on. 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