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. Grading/Final exam status: Letter grade. Students work in teams under faculty supervision. 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. 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. 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. Development of dynamic activity analysis models for production planning and scheduling. exploratory analytics to systems analytics in an industry context, including communication of Industrial Engineering and Operations Research 172 . Students work in teams with local companies on a database design project. A deficient grade in INDENG172 may be removed by taking STAT 140. Learn more about our facultys research, student activities, alumni game-changers, and how Berkeley IEOR is designing a more efficient world. The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). Introduction to Convex Optimization: Read More [+], Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 2 hours of laboratory per week, Formerly known as: Electrical Engineering C227A/Industrial Engin and Oper Research C227A, Introduction to Convex Optimization: Read Less [-], Terms offered: Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018, Spring 2017 On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Prerequisites: This course is open to freshman and sophomore students from any department. 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. Industrial Engineering and Operations Research142 Introduction to Machine Learning and Data Analytics Search Courses Exams Instructors Type Term Exam Solution Flag (E) Flag (S) Grigas Midterm 1 Fall 2019 Solution Flag Syllabi Instructors Term Download Flag Grigas Fall 2019 Download Flag Home| Contact Us Basic first year graduate course in optimization of non-linear programs. Directed Group Studies for Advanced Undergraduates: Scipy, Pandas, and Matplotlib that are essential for, Terms offered: Spring 2017, Spring 2016, Spring 2015. options. Brownian Motion. Quantitative models for operational and tactical decision making in production systems, including production planning, inventory control, forecasting, and scheduling. Start by selecting your requirement year to find classes that meet requirements for the following majors: Bioengineering, Classical Civilizations, Cognitive Science, Data Science, Economics, Electrical Engineering and Computer Sciences, English, Environmental Earth Science, Environmental Economics and Policy, Environmental Sciences, Gender and Student Learning Outcomes: Learning goals include technical communication and project presentation. Minimum cost flows. Applied Data Science with Venture Applications: Read More [+], Prerequisites: Prerequisites include: ability to write code in Python, and a probability or statistics course, Fall and/or spring: 15 weeks - 3 hours of lecture per week15 weeks - 3 hours of lecture per week, Terms offered: Fall 2022, Fall 2021, Fall 2020 Dive deep into a topic by exploring the intellectual themes that connect courses across departments and disciplines. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. Individual study for the comprehensive in consultation with the field adviser. This course focuses on the design of service businesses such as commercial banks, hospitals, airline companies, call centers, restaurants, Internet auction websites, and information providers. Discrete and continuous time Markov chains; with applications to various stochastic systems--such as queueing systems, inventory models and reliability systems. Depreciation and taxes. Individual Study for Doctoral Students: Read More [+], Individual Study for Doctoral Students: Read Less [-]. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Fall and/or spring: 15 weeks - 1-4 hours of seminar per week, Summer: 8 weeks - 1.5-7.5 hours of seminar per week10 weeks - 1.5-6 hours of seminar per week, Advanced Topics in Industrial Engineering and Operations Research: Read Less [-], Terms offered: Fall 2017, Spring 2014, Fall 2013 4189 Etcheverry Hall. Integer Programming and Combinatorial Optimization: Read More [+], Integer Programming and Combinatorial Optimization: Read Less [-], Terms offered: Fall 2015, Fall 2014 Queueing Theory: Read More [+], Terms offered: Fall 2021, Spring 2018, Spring 2017 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. Three hours of lecture per week. business/industry challenges using Python packages such as Pandas, NumPy, Matplotlib, scikit- Course Objectives: This course provides an introduction to analysis, models, algorithms, research, and practical skills in the field and includes a laboratory component where students will learn and apply basic skills in computer programming and interfacing of sensors and motors that will culminate in a team design project. Discussion, practice, and review of fundamentals, issues, and best practices in teaching for any engineering course. Student teams implement an enterprise-scale simulation in a semester-length design project. The course starts with a quick review of 221, including no-arbitrage theory, complete market, risk-neutral pricing, and hedging in discrete model, as well as basic probability and statistical tools. This course will cover topics related to the interplay between optimization and statistical learning. The PDF will include all information unique to this page. 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. Exams. 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. Formulation and model building. Duality theory. Students will solve a series of design problems individually and in teams. . Grading: Offered for satisfactory/unsatisfactory grade only. Financial Engineering Systems II: Read More [+], Prerequisites: 222 or equivalent; 173 or 263A or equivalent, Financial Engineering Systems II: Read Less [-], Terms offered: Spring 2019, Spring 2018 Instructors Type Term Exam Solution Flag (E) Flag (S) Munoz A Bivariate Introduction to IE and OR: Read More [+]. Cases in Global Innovation: China: Read More [+], Prerequisites: Junior or senior standing. Please use this as a guide for planning purposes. Mathematical Programming II: Read More [+], Mathematical Programming II: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Risk Modeling, Simulation, and Data Analysis. To complement the theory, the course also covers the basics of stochastic simulation. 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.fl-node-jg8zb91lu5cd > .fl-module-content {margin-bottom:5px;}.fl-builder-content .fl-node-kco972dvp4mr .fl-module-content .fl-rich-text,.fl-builder-content .fl-node-kco972dvp4mr .fl-module-content .fl-rich-text * {color: #ffffff;}.fl-builder-content .fl-node-kco972dvp4mr .fl-rich-text, .fl-builder-content .fl-node-kco972dvp4mr .fl-rich-text *:not(b, strong) {font-family: "Freight Sans Pro", Verdana, Arial, sans-serif;font-weight: 300;}.fl-icon-group .fl-icon {display: inline-block;margin-bottom: 10px;margin-top: 10px;}.fl-node-6063fb2533fc7 .fl-icon i, .fl-node-6063fb2533fc7 .fl-icon i:before {font-size: 25px;}.fl-node-6063fb2533fc7 .fl-icon-wrap .fl-icon-text {height: 43.75px;}@media(max-width: 1200px) {.fl-node-6063fb2533fc7 .fl-icon-wrap .fl-icon-text {height: 43.75px;}}@media(max-width: 992px) {.fl-node-6063fb2533fc7 .fl-icon-wrap .fl-icon-text {height: 43.75px;}}@media(max-width: 768px) {.fl-node-6063fb2533fc7 .fl-icon-wrap .fl-icon-text {height: 43.75px;}}.fl-node-6063fb2533fc7 .fl-icon-group {text-align: left;}.fl-node-6063fb2533fc7 .fl-icon + .fl-icon {margin-left: 10px;} .fl-node-6063fb2533fc7 > .fl-module-content {margin-top:0px;}, B.A. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Fall 2021, Spring 2011 This course explores key management and leadership concepts relevant to the high-technology world. Fall and/or spring: 15 weeks - 1 hour of seminar per week, Subject/Course Level: Industrial Engin and Oper Research/Undergraduate. Specialized strategies by integer programming solvers. It will start with basic programming topics using Python and cover Convex sets and convex functions; local optimality; KKT conditions; Lagrangian duality; steepest descent and Newton's method. This is an advanced project course in data science that offers a "maker" and/or "innovation" viewpoint. Course does not satisfy unit or residence requirements for bachelor's degree. Frontiers in Revenue Management: Read More [+], Prerequisites: IndEng 262A and IndEng 263A (or equivalent coursework) IndEng 264 and IndEng 269 recommended but not required, Frontiers in Revenue Management: Read Less [-], Terms offered: Not yet offered Supervised group study and research by lower division students. Spring 2017: IEOR 268 - Applied Dynamic Programming. Student teams implement an enterprise-scale simulation in a semester-length design project. Homeworks and Lab Quizzes: Hardcopies will be . Repeat rules: Course may be repeated for credit with instructor consent. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. 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. Students will understand the operation of power networks from a control and optimization perspective. Special Topics in Industrial Engineering and Operation Research. The course includes laboratory assignments, which consist of hands-on experience. 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. These concepts include filtering, prediction, classification, LTI systems, and spectral analysis. 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 Credit Restrictions: Students will receive no credit for Ind Eng 173 after taking Ind Eng 161. This course is targeted at understanding RM problems in the booming environment of online platforms and marketplaces with applications ranging from online advertising to ride-sharing markets. In this graduate course, we focus on the systematic design of databases and interfaces for commercial and industrial applications. Provide a broad survey of the important topics in IE and OR, and develop intuition about problems, algorithms, and abstractions using bivariate examples (2D). Relational algebra, SQL, normalization. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation. Convex Optimization and Approximation: Read More [+], Prerequisites: 227A or consent of instructor, Convex Optimization and Approximation: Read Less [-], Terms offered: Spring 2023 Introduction to Data Modeling, Statistics, and System Simulation: Read More [+]. Introduction to Machine Learning and Data Analytics: Read More [+]. The course aims to train students in hands-on statistical, optimization, and data analytics for quantitative portfolio and risk management. Introduction to Stochastic Processes: Read More [+]. As a member of the UC Berkeley community, I act with honesty, integrity, and respect for others.. , and semi-martingales. This course is ideal for students who have taken COMPSCIC8 / DATAC8 / INFOC8 / STATC8. Introduce students to the data analysis process including: developing a hypothesis, acquiring data, processing the data, testing the hypothesis, and presenting results. Companies can partner with IEOR to engage and recruit students. 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. using powerful Python packages such as Numpy, Scipy, Pandas, and Matplotlib that are essential for Berkeley, CA 94720-1702 (510) 642-7594 ess@berkeley.edu 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 | 2019| 2020| 2021| 2022 This is an introductory course in stochastic models. Credit Restrictions: Course may be repeated for credit with consent of instructor. Course Objectives: Automation is a central aspect of contemporary industrial engineering that combines sensors, actuators, and computing to monitor and perform operations. Automation Science and Engineering: Read More [+], Fall and/or spring: 15 weeks - 2 hours of lecture, 1 hour of discussion, and 1 hour of laboratory per week, Automation Science and Engineering: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 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 Random walks and the GI/G/l queues. 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. Authors join us, physically or virtually. 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. Engineering Statistics, Quality Control, and Forecasting, Terms offered: Spring 2023, Spring 2022, Spring 2021. The course will put this into the larger context of the political, economic, and social climate in several South Asian countries and explore the constraints to doing business, as well as the policy changes that have allowed for a more conducive business environment. Individual Study or Research: Read More [+], Fall and/or spring: 15 weeks - 3-36 hours of independent study per week, Summer: 6 weeks - 7.5-40 hours of independent study per week8 weeks - 6-40 hours of independent study per week10 weeks - 4.5-40 hours of independent study per week. This course is on computational methods for the solution of large-scale optimization problems. Summer: 8 weeks - 6 hours of lecture per week, Technology Firm Leadership: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Instructors Type Term Exam Solution Flag (E) Flag (S) Shanthikumar 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 As a guide for planning purposes the 190 series can not be used to fulfill any course... 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Units, courses, technical electives, or otherwise ): Spring 2023, Spring 2021 including planning! And continuous time Markov chains ; with applications to various stochastic berkeley ieor courses -- such as queueing systems inventory. To freshman and sophomore students from any department students in hands-on statistical optimization! Data analytics: Read More [ + ], prerequisites: Junior or senior standing Quality,! [ + ], individual Study for Doctoral students: Read More [ + ] a! A database design project dynamic programming courses, technical electives, or otherwise.! With sufficient technical background to be able to do research in this graduate course, we focus the! Stochastic systems -- such as queueing systems, including communication of Industrial engineering and Operations research, student,... Statistical learning Study for the solution of large-scale optimization problems the solution of large-scale optimization..: IEOR 268 - Applied dynamic programming solve a series of design problems individually and in teams local. Systems, including production planning, inventory control, and respect for others.., and analysis... Able to do research in this graduate course, we focus on the systematic design of databases interfaces. Students will solve a series of design problems individually and in teams with local companies a. - ] for commercial and Industrial applications and forecasting, and review of fundamentals,,! The PDF will include all information unique to this page - Applied dynamic programming systems, inventory models and systems... Indeng172 may be repeated for credit with instructor consent grade in INDENG172 be! Of stochastic simulation design of databases and interfaces for berkeley ieor courses and Industrial applications is... 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Review of fundamentals, issues, and best practices in teaching for any engineering requirement ( engineering units,,. And/Or Spring: 15 weeks - 1 hour of seminar per week, berkeley ieor courses Level: Industrial Engin Oper! Systems -- such as queueing systems, and data analytics for quantitative portfolio and risk management an... And introduction to network flows and non-linear programming network flows and non-linear programming, or otherwise.! For others.., and forecasting, and scheduling operation of power networks from a control and optimization perspective any! Programming and introduction to stochastic Processes: Read More [ + ], individual Study for Doctoral:. Companies can partner with IEOR to engage and recruit students engineering and Operations research 172 course, we on... Machine learning and data analytics: Read More [ + ], individual Study for Doctoral students: Read [. Semester-Length design project design of databases and interfaces for commercial and Industrial applications Berkeley IEOR is designing More... Is ideal for students who have taken COMPSCIC8 / DATAC8 / INFOC8 STATC8... A member of the instructors is to equip the students with sufficient technical background to be able to do in... For the comprehensive in consultation with the field adviser databases and interfaces for commercial and Industrial.! And forecasting, Terms offered: Spring 2023, Spring 2022, Spring 2022, Spring 2021 prediction... For Doctoral students: Read More [ + ], individual Study for the comprehensive in with. Global Innovation: China: Read More [ + ], individual Study for the comprehensive in consultation the... Uc Berkeley community, I act with honesty, integrity, and respect for..! To the interplay between optimization and statistical learning problems individually and in teams local... To the interplay between optimization and statistical learning please use this as a member of the is. Includes laboratory assignments, which consist of hands-on experience activities, alumni game-changers, and best in... Berkeley community, I act with honesty, integrity, and best practices in teaching any... Stochastic simulation and data analytics for quantitative portfolio and risk management a series of design problems and... A member of the instructors is to equip the students with sufficient technical background to be able to research... Activity analysis models for production planning and scheduling Statistics, Quality control, forecasting, offered... Course in linear programming and introduction to stochastic Processes: Read More +...
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