Optimization and Algorithms Machine Learning and Data Science Network Flows and Graphs: Read More [+], Prerequisites: 262A (may be taken concurrently), Terms offered: Spring 2022, Spring 2016, Spring 2015 In this graduate course, we focus on the systematic design of databases and interfaces for commercial and industrial applications. Group studies of selected topics. Related concepts of computer science tools and theoretical concepts are covered to support the project. To introduce students to advanced topics that are important to the successful application of machine learning methods in practice, include how methods for prediction are integrated with optimization models and modern optimization techniques for large-scale learning problems. 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. Fall and/or spring: 15 weeks - 1 hour of seminar per week, Subject/Course Level: Industrial Engin and Oper Research/Undergraduate. 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. Organize concepts and objectives covered in an engineering course.3. The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. 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. The Department of Industrial Engineering and Operations Research (IEOR) offers four graduate programs: a Master of Engineering (MEng), a Master of Science (MS), a Master of Analytics (MAnalytics), and a PhD. doctoral students formulate their research designs. While these two programs share some core technical courses, the IEOR Master of Engineering program prepares students for engineering leadership and offers a curriculum with a balance of management and technical content. This course will cover topics related to the interplay between optimization and statistical learning. 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. 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. Student Learning Outcomes: Learn more about Industrial Engineering and Operations Research. Stochastic simulation ideas will be introduced and used to obtain the risk-neutral geometric Brownian motion values for certain types of Asian, barrier, and lookback options. This year, Berkeley IEOR alum Sujit Chakravarthy, is making a $25,000 Big Match to support the IEOR Fund. Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. BerkeleyX offers interactive online classes and MOOCs from the worlds best universities. learn, Bokeh, and relevant optimization and simulation software. 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. Final exam not required. Special Topics in Industrial Engineering and Operation Research: Read More [+], Prerequisites: Upper level standing or graduate student, Fall and/or spring: 15 weeks - 2-3 hours of lecture per week, Summer: 6 weeks - 5-7.5 hours of lecture per week10 weeks - 3-4.5 hours of lecture per week, Special Topics in Industrial Engineering and Operation Research: Read Less [-], Terms offered: Spring 2014, Fall 2008, Spring 2008 Instructor Professor Robert C. Leachman 510-517-6113 leachman[at]ieor.berkeley.edu Office hours: MWF 11:00-12:00pm Online via Zoom . Individual study in consultation with the major field adviser, intended to provide an opportunity for qualified students to prepare themselves for the various examinations required of candidates for the Ph.D. (and other doctoral degrees). Lectures and appropriate assignments on fundamental or applied topics of current interest in industrial engineering and operations research. Students will work in teams on projects and build solutions to Course Objectives: This course provides an introduction to the field of Industrial Engineering and Operations Research through a series of lectures by IEOR faculty. Design and development of effective industrial production planning systems. Concentrations - UC Berkeley IEOR Department - Industrial Engineering & Operations Research Home / Academics / Master of Engineering / Concentrations Master of Engineering Apply Ranked #2 in the nation! It is applied to a broad range of applications from manufacturing to transporation to healthcare. Portfolio optimization problems will be considered both from a mean-variance and from a utility function point of view. optimization methods using software packages, and will require some programming. Renewal reward processes with application to inventory, congestion, and replacement models. 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. Semi-Markov processes with emphasis on application. Practice fair and helpful evaluation of student work.After completion of the course, GSIs will be able to perform the following course-related tasks: Applied Stochastic Process II: Read More [+], Applied Stochastic Process II: Read Less [-], Terms offered: Spring 2017, Spring 2016, Spring 2015 Berkeley Seminars are offered in all campus departments, and topics vary from department to department and semester to semester. Optimization Analytics: Read More [+], Prerequisites: Basic analysis and linear algebra, and basic computer skills and experience, Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of laboratory per week, Terms offered: Fall 2022, Fall 2021, Fall 2020 Credit Restrictions: Students will receive no credit for INDENG156 after completing INDENG256. Repeat rules: Course may be repeated for credit without restriction. 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. Summer: 2 weeks - 15 hours of lecture and 10 hours of laboratory per week, Subject/Course Level: Industrial Engin and Oper Research/Graduate, Terms offered: Spring 2023, Fall 2022, Spring 2022 Application of systems analysis and industrial engineering to the analysis, planning, and/or design of industrial, service, and government systems. The course deals with discrete optimization problems and their complexity. The first part of the course will cover statistical modeling procedures that can be defined as the minimizer of a suitable optimization problem. 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 Grading/Final exam status: Offered for pass/not pass grade only. UC Berkeley's IEOR Department is at the forefront of optimization research. 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. 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. Logistics Network Design and Supply Chain Management: paths, project management and equipment replacement. Prerequisites: IEOR 165 or equivalent course in statistics. You can check their website here for information about their upcoming classes. Probability and Risk Analysis for Engineers: Read More [+]. Continuous time Markov chains. The goal is for students to develop the experience and intuition to gather and build new datasets and answer substantive questions. with risk-neutral pricing in continuous time models. Control and Optimization for Power Systems: Read Less [-], Terms offered: Spring 2009, Spring 2007, Spring 2006 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 Undergraduate Field Research in Industrial Engineering: Directed Group Studies for Advanced Undergraduates. recommendations. 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 conducting business, globalizing a company product or service, or investing in South Asia. Degree Programs Industrial Engineering and Operations Research Industrial Engineering and Operations Research About the Program Bachelor of Science (BS) The Bachelor of Science (BS) degree in Industrial Engineering and Operations Research (IEOR) is designed to prepare students for technical careers in production or service industries. Conditional Expectation. These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and predictive models characteristic of each subfield. 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 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. descriptive, predictive, and prescriptive analytics. Learn more. 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 . Simulation for Enterprise-Scale Systems: Read More [+]. This course will introduce graduate and upper division undergraduate students to modern methods for simulating discrete event models of complex stochastic systems. Students will be exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses. The simplex method; theorems of duality; complementary slackness. Operations Research and Management Science Honors Thesis: Read More [+], Terms offered: Spring 2023, Fall 2022, Spring 2022 To complement the theory, the course also covers the basics of stochastic simulation. 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 probability designed to develop a good understanding of uncertain phenomena and the mathematical tools used to model and analyze it. New issues raised by the World Wide Web. Advanced graduate course for Ph.D. students interested in pursuing a professional/research career in financial engineering. Course topics include an introduction to polyhedral theory, cutting plane methods, relaxation, decomposition and heuristic approaches for large-scale optimization problems. Survey of solution techniques and problems that have formulations in terms of flows in networks. Course Information. The field has made significant strides on both theoretical and practical fronts. 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. Enrollment restrictions apply. 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 Operations Research and Management Science Honors Thesis. Course does not satisfy unit or residence requirements for bachelor's degree. Through art and film programs, collections and research resources, BAM/PFA is the visual arts center of UC Berkeley. Mathematical Programming II: Read More [+], Mathematical Programming II: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Different methods of evaluation of alternatives. 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. Have students communicate their ideas and solutions effectively in written reports. The course is intended for graduate students at the Masters level looking for a concrete introduction IEOR 160: Nonlinear and Discrete Optimization Professor Javad Lavaei, UC Berkeley Instructor: Javad Lavaei Time: Fridays, 10am-12pm Location: 159 Mulford TAs: SangWoo Park (spark111 AT berkeley.edu) and Yatong Bai (yatong_bai AT berkeley.edu) Grader: Natalie Andersson (natalieandersson AT berkeley.edu) Watch, listen, and learn. and a group project. The Black-Scholes option-pricing formula will be derived and studied. To train students in how to actually apply each method that is discussed in class, through a series of labs and programming exercises.5. This course introduces unconstrained and constrained optimization with continuous and discrete domains. Familiarity with algorithm design and mathematical maturity recommended, Fundamentals of Revenue Management: Read Less [-], Terms offered: Fall 2020, Fall 2019, Fall 2018 Introduction to network flows models. Specialized strategies by integer programming solvers. Risk Modeling, Simulation, and Data Analysis. Discrete and continuous time Markov chains; with applications to various stochastic systems--such as queueing systems, inventory models and reliability systems. Mathematical and computer methods for design, planning, scheduling, and control in manufacturing and distribution systems. 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. Over the duration of this course, students will examines case studies of early, mid-stage, and large-scale enterprises as they seek to start a new venture, introduce a new product or service, or capitalize on global economic trends to enhance their existing business. This course is geared towards understanding operational, strategic, and tactical aspects of supply chain man agement. Consideration of technical and economic aspects of equipment and process design. Spring 2017: IEOR 258 - Control and Optimization for Power Systems. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. 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 China market, or domestic Chinese companies seeking to adapt a U.S. or western business model to the China market. Supervised independent study for lower division students. Alternate formulations for integer optimization: strength of Linear Programming relaxations. 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. Study of algorithms for non-linear optimization with emphasis on design considerations and performance evaluation. Introduction to Martinjales. 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. written paper is also required. develop custom Python scripts and functions to perform analytic computations; South Asian companies seeking to adapt a U.S or western business model. Capital sources and their effects. Students will gain experience with a commercial database management system and will work in teams with Control and Optimization for Power Systems: Read More [+]. [IEOR 130] Questions for Homework 1 This course is on computational methods for the solution of large-scale optimization problems. 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. The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). Formulation and model building. Technology Firm Leadership: Read More [+]. Probabilitybackgroundwith Industrial Engineering173 orequivalentisrecommended, Applied Stochastic Process I: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 Grading: Offered for satisfactory/unsatisfactory grade only. Branch and Bound; Cutting plane methods; polyhedral theory. The main goal is to develop proficiency in common optimization modeling languages, and learn how to integrate them with underlying optimization solvers. Insure students become familiar with the fundamental similarities and differences among simulation software packages. Terms offered: Spring 2018, Fall 2016, Spring 2016 Techniques for yield analysis, process control, inspection sampling, equipment efficiency analysis, cycle time reduction, and on-time delivery improvement. This is an introductory course in stochastic models. To train students in modeling of integer optimization problems; Minimum cost flows.
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