Please use this as a guide for planning purposes. The main goal is to develop proficiency in common optimization modeling languages, and learn how to integrate them with underlying optimization solvers. This Freshman-level Introductory course will provide an intuitive overview of the fundamental problems addressed and methods in the fields of Industrial Engineering and Operations Research including Constrained Optimization, Human Factors, Data Analytics, Queues and Chains, and Linear Programming. models characteristic of each subfield. Search Courses. Credit Restrictions: Course may be repeated for credit with consent of instructor. Welcome to UC Berkeleys Industrial Engineering and Operations Research Department. 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. The field has made significant strides on both theoretical and practical fronts. Operations Research and Management Science Honors Thesis: Read More [+], Terms offered: Spring 2023, Fall 2022, Spring 2022 A Have students communicate their ideas and solutions effectively in written reports. It will start with basic programming topics using Python and cover Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Spring 2017, Fall 2014, Spring 2014 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. To introduce students to the core concepts of optimization Copyright 2023-24, UC Regents; all rights reserved. These topics include complexity analysis of algorithms and its drawbacks; solving a system of linear integer equations and inequalities; strongly polynomial algorithms, network flow problems (including matching and branching); polyhedral optimization; branch and bound and lagrangean relaxation. 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. Describe different mathematical abstractions used in IEOR (e.g., graphs, queues, Markov chains), and how to use these abstractions to model real-world problems. Topics include the types of problems that can be solved by such methods. The course will discuss applications such as dieting, scheduling, and transportation. The course is focused first on developing an open-ended-real world project relating to data science. , and semi-martingales. Teach students how to model random processes and experiment with simulated systems. Relational algebra, SQL, normalization. Convex optimization as a systematic approximation tool for hard decision problems. Repeat rules: Course may be repeated for credit without restriction. Since 1909, distinguished guests have visited UC Berkeley to speak on a wide range of topics, from philosophy to the sciences. Industrial Design and Human Factors: Read More [+], Industrial Design and Human Factors: Read Less [-], Terms offered: Spring 2023, Spring 2022, Fall 2020 Prerequisites: No prerequisites except some Python programming skills, which can be met by COMPSCIC8 (or any other Python-based course), Introduction to Optimization Modeling: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 This is an advanced project course in data science that offers a "maker" and/or "innovation" viewpoint. Uncertainty; preference under risk; decision analysis. Credit Restrictions: Students will receive 2 units for 120 after taking Civil Engineering 167. Selected topics in mathematical programming. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. Introductory course on design, programming, and statistical analysis of simulation methods and tools for enterprise-scale systems such as traffic and computer networks, health-care and financial systems, and factories. understand relevant mathematical concepts that are used in systems that process data; Prerequisites: Prerequisites include the ability to write code in Python, and a probability or statistics course. About a third of the course will be devoted to system modeling, with the remaining two-thirds concentrating on simulation experimental design and analysis. 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. 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 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. Operations Research & Management Science, B.S. Credit Restrictions: Students will receive no credit for Ind Eng 173 after taking Ind Eng 161. Student Learning Outcomes: LEARNING GOALS Course Objectives: Provide an introduction to the field of Industrial Engineering and Operations Research through a series of lectures. 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. Supply chain analysis is the study of quantitative models that characterize various economic trade-offs in the supply chain. These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and predictive models characteristic of each subfield. Students work in teams with local companies on a database design project. Engineering Statistics, Quality Control, and Forecasting, Terms offered: Spring 2023, Spring 2022, Spring 2021. Course Objectives: business/industry challenges using Python packages such as Pandas, NumPy, Matplotlib, scikit- By discussing various applications in science and engineering, students will be able to model many real world problems where uncertainty plays an important role. Immerse yourself in performances and programs from around the world that explore the intersections of education and the performing arts. 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 Introduce students to the data analysis process including: developing a hypothesis, acquiring data, processing the data, testing the hypothesis, and presenting results. They will also manage hypothetical portfolios throughout the course. Industrial Engineering & Operations Research, Management, Entrepreneurship & Technology, Ph.D. Industrial Engineering & Operations Research, Applied Data Science with Venture Applications, Logistics Network Design and Supply Chain Management, Engineering Statistics, Quality Control, and Forecasting, Probability and Risk Analysis for Engineers. advanced analytics courses. 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 [+] Topics include: preparing a syllabus; public speaking and coping with language barriers; creating effective slides and exams; differing student learning styles; grading; encouraging diversity, equity, and inclusion; ethics; dealing with conflict and misconduct; and other topics relevant to serving as an effective teaching assistant. Brownian Motion. Spring 2017: IEOR 258 - Control and Optimization for Power Systems. 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. To carefully present the statistical and computational assumptions, trade-offs, and intuition underlying each method discussed so that students will be trained to determine which techniques are most appropriate for a given problem.3. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Spring 2013, Spring 2012, Spring 2011 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. These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and predictive models characteristic of each subfield. Grading Based on: 30% Class Attendance and Participation. for use in analytics applications as well as potentially conducting research in the area. 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 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. Instructor Professor Robert C. Leachman 510-517-6113 leachman[at]ieor.berkeley.edu Office hours: MWF 11:00-12:00pm Online via Zoom . Applied Stochastic Process II: Read More [+], Applied Stochastic Process II: Read Less [-], Terms offered: Spring 2017, Spring 2016, Spring 2015 Students will be exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses. Learn more about our facultys research, student activities, alumni game-changers, and how Berkeley IEOR is designing a more efficient world. 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. 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 On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Conditional Expectation. Industrial Engineering and Operations Research 172 . Students will work in teams on projects and build solutions to With the growing complexity of providing healthcare, it is increasingly important to design and manage health systems using engineering and analytics perspectives. Cal Students: Please apply with your CalCentral berkeley.edu email by 12/5/2022 or 1/5/2023 PST to receive . 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. 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. use Python and core scienti IEOR leverages computing to better manage the massive amounts of information available today. This highly-applied course surveys a variety of key of concepts and tools that are useful for designing and building applications that process data signals of information. Supply Chain Innovation, Strategy, and Analytics: Read More [+], Prerequisites: Introductory course on Production and Inventory Control or Operations Management, Supply Chain Innovation, Strategy, and Analytics: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Supervised Group Study and Research: Read More [+]. 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. 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. Applications will be given in such areas as reliability theory, risk theory, inventory theory, financial models, and computer science, among others. Directed Group Studies for Advanced Undergraduates: Scipy, Pandas, and Matplotlib that are essential for, Terms offered: Spring 2017, Spring 2016, Spring 2015. options. Risk Modeling, Simulation, and Data Analysis: Supply Chain Innovation, Strategy, and Analytics. Concentrating on simulation experimental design and analysis the field has made significant strides on theoretical... For hard decision problems welcome to UC Berkeleys Industrial Engineering and Operations Department! Analysis is the study of quantitative models that characterize various economic trade-offs the! To system modeling, with the remaining two-thirds concentrating on simulation experimental and. The field has made significant strides on both theoretical and practical fronts first on developing an world. Goal of the course will discuss applications such as dieting, scheduling, and predictive models characteristic each! Use in analytics applications as well as potentially conducting research in the chain! 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