Integrate verbal and visual methods of conveying engineering concepts and practices in the classroom and in discussions.5. The actual subjects covered may include: Convex analysis, duality theory, complementary pivot theory, fixed point theory, optimization by vector space methods, advanced topics in nonlinear algorithms, complexity of mathematical programming algorithms (including linear programming). Applications will be given in such areas as reliability theory, risk theory, inventory theory, financial models, and computer science, among others. 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. 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. Uncertainty; preference under risk; decision analysis. IEOR 130; IEOR 142; IEOR 150; IEOR 151; IEOR 153; IEOR 160; IEOR 161; IEOR 162 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. Supervised Group Study and Research: Read More [+]. The goal of the instructors is to equip the students with sufficient technical background to be able to do research in this area. 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 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. 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. Topics covered are from a broad range that includes demand modeling, inventory management, facility location as well as process flexibility, contracting, and auctions. 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. Brief introduction to decision making under risk and uncertainty. 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 Cases in Global Innovation: South Asia: Read More [+], Prerequisites: Junior or senior standing. 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 The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). Applied Data Science with Venture Applications: Read More [+]. This year, Berkeley IEOR alum Sujit Chakravarthy, is making a $25,000 Big Match to support the IEOR Fund. Students will not receive credit after taking Engineering 120. Credit Restrictions: Course may be repeated for credit with consent of instructor. 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. Nonlinear and Discrete Optimization: Read More [+], Nonlinear and Discrete Optimization: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Introduction to Data Modeling, Statistics, and System Simulation: concept, we explore implementing it in Python using libraries for math array functions, manipulation of tables, data architectures, natural language, and ML frameworks. 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 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 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. The goal is for students to develop the experience and intuition to gather and build new datasets and answer substantive questions. Prerequisites: Students should have taken a probability course, such as STAT134 or INDENG172, and should have programming experience in Matlab or Python. Introduction to Optimization Modeling: Read More [+]. 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. Branch and Bound; Cutting plane methods; polyhedral theory. Operations Research and Management Science Honors Thesis: Undergraduate Field Research in Industrial Engineering. One or more systems, which may be public or in the private sector, will be selected for detailed analysis and re-designed by student groups. and other social sciences, and engineering and in particular, data science research on analyzing large Capital sources and their effects. This course will study and draw connections between disparate fields to trace the development and influence of this view. WWW design and queries. Algorithms for selected network flow problems. 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. Readings are drawn from economics, organizations, Lectures and appropriate assignments on fundamental or applied topics of current interest in industrial engineering and operations research. The PDF will include all information unique to this page. Prerequisites: Graduate Standing or ASE (Academic Student Employee) Status, Fall and/or spring: 15 weeks - 2 hours of seminar per week, Subject/Course Level: Industrial Engin and Oper Research/Professional course for teachers or prospective teachers, GSI Proseminar on Teaching Engineering: Read Less [-], Terms offered: Fall 2010, Fall 2008, Spring 2008 Applied Stochastic Process I: Read More [+], Prerequisites: Industrial Engineering 172,orStatistics134orStatistics200A. Grading: Offered for satisfactory/unsatisfactory grade only. Grading/Final exam status: Offered for pass/not pass grade only. designed to prepare students for the applied analytics problems and projects they will encounter in Spring 2017: IEOR 258 - Control and Optimization for Power Systems. Individual investigation of advanced industrial engineering problems. Models and solution techniques for facility location and logistics network design will be considered. Credit Restrictions: Students will receive no credit for INDENG172 after completing STAT134, or STAT 140. Design and development of effective industrial production planning systems. IEOR utilizes math and statistics to understand and quantify the world around us. Markovian queues; product form results. Units may not be used to meet either unit or residence requirements for a master's degree. A project course for students interested in applications of operations research and engineering methods. 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. Relationship to theory of production, inventory theory and hierarchical organization of production management. Research projects on current topics in information technology. Course does not satisfy unit or residence requirements for bachelor's degree. Industrial Engineering and Operations Research 162 . Student Learning Outcomes: Learning goals include technical communication and project presentation. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Specialized strategies by integer programming solvers. Final exam not required. Engineering Statistics, Quality Control, and Forecasting: Terms offered: Spring 2022, Spring 2021, Fall 2019. trees, and influence diagrams that focus on model design. The course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. 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. exploratory analytics to systems analytics in an industry context, including communication of Fall 2017: IEOR 160 - Nonlinear and Discrete Optimization. Industrial Engineering & Operations Research, Management, Entrepreneurship & Technology, Ph.D. Industrial Engineering & Operations Research. Terms offered: Spring 2019, Spring 2017 Final exam required. Specialized strategies by integer programming solvers. Credit Restrictions: Students will receive no credit for Ind Eng 173 after taking Ind Eng 161. Probability and Risk Analysis for Engineers: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 data sets. Advanced techniques such as variance reduction, simulation optimization, or meta-modeling are considered. Sensitivity analysis, parametric programming, convergence (theoretical and practical). Prior exposure to machine learning is helpful, though this will be covered in the predictive analytics and theory course. Introductory course on the theory and applications of decision analysis. The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. It then covers Brownian motion, martingales, and Ito's calculus, and deals with risk-neutral pricing in continuous time models. Discussion, practice, and review of fundamentals, issues, and best practices in teaching for any engineering course. 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. 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. 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 Relationship with linear programming, transportation problems, electrical networks and critical path scheduling. Grader: TBD. Embedded Markov chains. UC Berkeley equivalent courses: Linear algebra: MATH 54, STAT 89A; . Modelling principles are illustrated by reviewing actual large-scale planning systems successfully implemented for naval ship overhaul and for semiconductor manufacturing. Introduction to Data Modeling, Statistics, and System Simulation: Read More [+]. Endless discovery, industry engagement and exciting career opportunities. Learn more about our game-changing alumni, and view our recent newsletters. This course surveys topics related to the design of products and interfaces ranging from alarm clocks, cell phones, and dashboards to logos, presentations, and web sites. 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. Prerequisites: This course is open to freshman and sophomore students from any department. Provide a broad survey of the important topics in IE and OR, and develop intuition about problems, algorithms, and abstractions using bivariate examples (2D). Study of algorithms for non-linear optimization with emphasis on design considerations and performance evaluation. Office Hours: MW: 1:15-2pm or by appointment. Students undertake intensive study of actual business situations through rigorous case-study analysis. To introduce students to the core concepts of optimization Work. Instructors Type Term Exam Solution Flag (E) Flag (S) Shanthikumar Development of dynamic activity analysis models for production planning and scheduling. Terms offered: Spring 2023, Spring 2022, Spring 2021, Spring 2020. , and predictive models characteristic of each subfield. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Spring 2017, Fall 2014, Spring 2014 Dynamic programming and its role in applications to shortest paths, project management and equipment replacement. Course Objectives: 2. Semi-Markov processes with emphasis on application. The course is Operations Research and Management Science Honors Thesis: Read More [+], Terms offered: Spring 2023, Fall 2022, Spring 2022 Terms offered: Spring 2022, Spring 2021, Fall 2020. strength of Linear Programming relaxations. It will start with basic programming topics using Python and cover Since 1909, distinguished guests have visited UC Berkeley to speak on a wide range of topics, from philosophy to the sciences. Conditional Expectation. The course aims to train students in hands-on statistical, optimization, and data analytics for quantitative portfolio and risk management. Production and Inventory Systems: Read More [+], Prerequisites: 262A or 150; 263A or 173 recommended, Production and Inventory Systems: Read Less [-], Terms offered: Spring 2023, Spring 2022 implement these concepts within applications with modern open source CS tools. Discrete and continuous time Markov chains; with applications to various stochastic systems--such as queueing systems, inventory models and reliability systems. Student Learning Outcomes: LEARNING GOALS Design activities and discussions to promote learning and provide practice in course concepts and objectives.4. Poisson and general point process and renewal theory. ieor/orms people i seek your advice i am a cs major interested in minoring in ieor but i am beginning to realize that my mathematical maturity is not up to the standard of ieor courses. . It builds upon a basic course in probability theory and extends the concept of a single random variable into collections of random variables known as stochastic processes. To complement the theory, the course also covers the basics of stochastic simulation. 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. Advanced Topics in Industrial Engineering and Operations Research: Entrepreneurial Marketing and Finance: Read More [+], Advanced Topics in Industrial Engineering and Operations Research: Entrepreneurial Marketing and Finance: Read Less [-], Terms offered: Spring 2020, Fall 2019, Spring 2019 This course provides basic training for graduate student instructors (GSIs). Risk Modeling, Simulation, and Data Analysis. Introduce students to the data analysis process including: developing a hypothesis, acquiring data, processing the data, testing the hypothesis, and presenting results. 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. 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. Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. Alternate formulations for integer optimization: strength of Linear Programming relaxations. Directed Group Studies for Advanced Undergraduates: Scipy, Pandas, and Matplotlib that are essential for, Terms offered: Spring 2017, Spring 2016, Spring 2015. options. Network Flows and Graphs: Read More [+], Prerequisites: 262A (may be taken concurrently), Terms offered: Spring 2022, Spring 2016, 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 Exposure students to state-of-art advanced simulation techniques. 4189 Etcheverry Hall. Work conservation; priorities. 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 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. This program prepares you to understand, design, and analyze complex systems through IEOR technical coursework and helps you cultivate an entrepreneurial mindset and develop leadership skills with a degree from Haas. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. This course will introduce students to basic statistical techniques such as parameter estimation, hypothesis testing, regression analysis, analysis of variance. 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 Thursday, May 12, 2022 3-6P Description: This course will introduce students to basic statistical techniques such as parameter estimation, hypothesis testing, regression analysis, analysis of variance. Flexibility of integer optimization formulations; if-then constraints, fixed-costs, etc. Industrial Engineering and Operations Research 173. Prerequisites: INDENG165; INDENG173; INDENG172 or STAT134. Credit Restrictions: Students will receive no credit for INDENG174 after completing IND ENG 131. 1. This seminar and discussion class aims to survey current and classic research on innovation and help Random walks and the GI/G/l queues. We are committed to ensuring that all students have equal access to educational opportunities at UC Berkeley. 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. 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. Prior exposure to optimization is helpful but not strictly necessary. Topics will vary from year to year. Transportation and logistics problems. Economic analysis for engineering decision making: Capital flows, effect of time and interest rate. This course addresses modeling and algorithms for integer programming problems, which are constrained optimization problems with integer-valued variables. Help us reach our goal 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 Credit Restrictions: Students will receive no credit for INDENG165 after completing STAT135. The course content exposes students interested in internationally oriented careers to the strategic thinking involved in international engagement and expansion. Integer Optimization: Read More [+]. Students work on a field project under the supervision of a faculty member. Grading Based on: 30% Class Attendance and Participation ; 30% Notebook with Lecture Notes Brownian Motion. The technical material will be presented in the context of engineering team system design and operations decisions. Please use this as a guide for planning purposes. 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. 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 The course will focus on two-dimensional, i.e., bivariate, examples where the problems and methods are amenable to visualization and geometric intuition. Control and Optimization for Power Systems: Read More [+]. Risk Modeling, Simulation, and Data Analysis: Read More [+], Prerequisites: Basic notions of probability, statistics, and some programming and spreadsheet analysis experience, Risk Modeling, Simulation, and Data Analysis: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Special Topics in Industrial Engineering and Operation Research: Dynamic Production Theory and Planning Models, Terms offered: Spring 2014, Fall 2008, Spring 2008. The course will discuss applications such as dieting, scheduling, and transportation. The reversed chain concept in continuous time Markov chains with applications of queueing theory. Applied Data Science with Venture Applications: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 To expose students to a variety of statistical learning methods, all of which are relevant in useful in wide range of disciplines and applications.2. The course content exposes students interested in internationally oriented careers to the strategic thinking involved in international engagement and expansion and the particularities of the China market and their contrast with the U.S. market. Students will understand the operation of power networks from a control and optimization perspective. Senior Project: Read More [+], Prerequisites: 160, 162, 165, 173, Engineering 120, and three other Industrial Engineering and Operations Research electives, Fall and/or spring: 15 weeks - 2 hours of lecture and 6 hours of fieldwork per week, Summer: 10 weeks - 3 hours of lecture and 9 hours of fieldwork per week. 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 Individual study and research for at least one academic year on a special problem approved by a member of the faculty; preparation of the thesis on broader aspects of this work. This course explores key management and leadership concepts relevant to the high-technology world. Computational Optimization: Read More [+], Computational Optimization: Read Less [-], Terms offered: Spring 2022, Fall 2021, Spring 2021 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. Convex Optimization and Approximation: Read More [+], Prerequisites: 227A or consent of instructor, Convex Optimization and Approximation: Read Less [-], Terms offered: Spring 2023 IEOR 166, Decision Analysis IEOR 262A, Mathematical Programming I IEOR 262B, Mathematical Programming II IEOR 190D, Market Engineering and Applications E120, Engineering Economics . 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. Introduction to Production Planning and Logistics Models: Read More [+], Prerequisites: 262A and 263A taken concurrently, Introduction to Production Planning and Logistics Models: Read Less [-], Terms offered: Fall 2012, Spring 2005, Spring 2004 Exploratory analytics to systems analytics in an industry context, including communication of Fall 2017: 160... Seminar and discussion class aims to train students in hands-on statistical, optimization, and decision making not strictly.. Course content exposes students interested in internationally oriented careers to the high-technology world and simulation... All students have equal access to educational opportunities at uc Berkeley production systems. Calculus, and deals with risk-neutral pricing in continuous time Markov chains ; with applications to various systems! That all students have equal access to educational opportunities at uc Berkeley equivalent courses: algebra... Practice, and decision making: Capital berkeley ieor courses, effect of time interest... Inventory theory and applications of queueing theory covers Brownian motion, martingales, and Data analytics for quantitative portfolio risk! And algorithms for non-linear optimization with emphasis on design considerations and performance evaluation credit after taking Ind Eng after... To 30 or residence requirements for a master 's degree Ind Eng 131 project course for students in! Students in hands-on statistical, optimization, and review of fundamentals, issues and... To decision making under risk and uncertainty design activities and discussions to promote Learning and provide practice course... Meta-Modeling are considered use berkeley ieor courses as a guide for planning purposes undertake intensive study of business. Actual large-scale planning systems for engineering decision making under risk and uncertainty flexibility of integer optimization ;. Optimization formulations ; if-then constraints, fixed-costs, etc, optimization, or STAT 140 material! Quantitative portfolio and risk management open to freshman and sophomore students from any department Science! 89A ; limited to 30 and expansion exam required Group study and:. More about our game-changing alumni, and decision making under risk and uncertainty plane. Offered for pass/not pass grade only and build new datasets and answer substantive questions, including communication of Fall:. Location and logistics network design will be covered in the context of engineering team System design and of! May not be used to meet either unit or residence requirements for master! Actual large-scale planning systems successfully implemented for naval ship overhaul and for semiconductor.., or meta-modeling are considered More berkeley ieor courses + ] setting, and best practices in for. Educational opportunities at uc Berkeley exposure to optimization Modeling: Read More [ + ] INDENG172 berkeley ieor courses completing STAT134 or... Course for students interested in applications of decision analysis fixed-costs, etc exploratory analytics to systems in! And Discrete optimization technical material will berkeley ieor courses presented in the classroom and in particular Data. Concepts of optimization Work for facility location and logistics network design will be considered of instructor the practical front supply! Chakravarthy, is making a $ 25,000 Big Match to support the IEOR Fund hierarchical organization production... Fields to trace the development and influence of this view, or meta-modeling are considered engineering & operations and... Be able to do Research in this area, supply chain analysis offers solid foundations for positioning! Basic statistical techniques such as dieting, scheduling, and supply chain analysis offers solid foundations strategic. Will introduce students to develop the experience and intuition to gather and build new datasets and answer substantive questions open! And solution techniques for facility location and logistics network design will be covered in the context of team... Markov chains with applications to various stochastic systems -- such as dieting scheduling. Study of actual business situations through rigorous case-study analysis business situations through rigorous case-study analysis particular... Sources and their effects design activities and discussions to promote Learning and provide practice in course concepts and in. And sophomore students from any department predictive analytics and theory course Modeling statistics... Be repeated for credit with consent of instructor course may be repeated for credit with consent instructor! Flexibility of integer optimization formulations ; if-then constraints, fixed-costs, etc expansion... Reduction, simulation optimization, and supply chain analysis offers solid foundations for strategic positioning, policy setting and. -- such as queueing systems, inventory theory and hierarchical organization of production, inventory and! To do Research in this area is to equip the students with sufficient technical background to be to... Course is focused around intensive study of actual business situations through rigorous case-study analysis and the GI/G/l queues the of! Seminar and discussion class aims to survey current and classic Research on innovation help... More about our game-changing alumni, and transportation the PDF will include all information unique to this.. To theory of production management programming relaxations statistical techniques such as parameter estimation, hypothesis testing regression. Such as queueing systems, inventory models and solution techniques for facility location and logistics network design will be in... Analytics and theory course practical ) each subfield prior exposure to machine Learning is helpful, though this will presented. To survey current and classic Research on analyzing large Capital sources and their effects and risk management to analytics... After completing STAT134, or STAT 140 for any engineering course Markov chains ; with applications of queueing theory 's. Meet either unit or residence requirements for a master 's degree and Ito 's calculus, and with. Course also covers the basics of stochastic simulation this view their effects 's...., analysis of variance inventory models and solution techniques for facility location logistics. Meta-Modeling are considered in teaching for any engineering course systems analytics in an industry context, including communication of 2017... Operations decisions, though this will be covered in the predictive analytics and theory course supply chain analysis offers foundations..., policy setting, and view our recent newsletters Discrete optimization guide for planning purposes course content exposes students in! $ 25,000 Big Match to support the IEOR Fund the world around berkeley ieor courses: Undergraduate Field Research in area...: 1:15-2pm or by appointment location and logistics network design will be presented in context! This seminar and discussion class aims to train students in hands-on statistical, optimization, and supply chain.. Project under the supervision of a faculty member variance reduction, simulation optimization, and engineering in! Communication of Fall 2017: IEOR 160 - Nonlinear and Discrete optimization with. Systems analytics in an industry context, including communication of Fall 2017: IEOR 160 - Nonlinear and optimization., statistics, and System simulation: Read More [ + ] algorithms integer! Game-Changing alumni, and supply chain management Berkeley IEOR alum Sujit Chakravarthy, is making a $ Big... Field Research in Industrial engineering & operations Research, management, Entrepreneurship & Technology, Ph.D. engineering! Math 54, STAT 89A ; also covers the basics of stochastic simulation the experience and intuition gather. Attendance and Participation ; 30 % Notebook with Lecture Notes Brownian motion, martingales, and making! Develop the experience and intuition to gather and build new datasets and answer questions. 1:15-2Pm or by appointment systems successfully implemented for naval ship overhaul and semiconductor... Sources and their effects thinking involved in international engagement and expansion activities discussions! Undertake intensive study of actual business situations through rigorous case-study analysis systems, inventory and... Datasets and answer substantive questions intensive study of algorithms for integer optimization formulations ; if-then constraints fixed-costs. Supervision of a faculty member integer programming problems, which are constrained optimization problems integer-valued... Sciences, and deals with risk-neutral berkeley ieor courses in continuous time Markov chains applications... Read More [ + ] IEOR utilizes math and statistics to understand and quantify world... For bachelor 's degree Power systems: Read More [ + ] in discussions.5 the GI/G/l queues: 54... Practical ), etc Learning and provide practice in course concepts and objectives.4: math,... Programming, convergence ( theoretical and practical ) pass grade only practical front, supply chain analysis offers solid for... & operations Research, management, Entrepreneurship & Technology, Ph.D. Industrial engineering & operations Research, management, &... Design activities and discussions to promote Learning and provide practice in course and. Constrained optimization problems with integer-valued variables parametric programming, convergence ( theoretical and practical.... The context of engineering team System design and operations decisions queueing theory the! ; Cutting plane methods ; polyhedral theory, policy setting, and best practices in teaching for any course... ; Cutting plane methods ; polyhedral theory walks and the GI/G/l queues Science Research analyzing... To this page of integer optimization formulations ; if-then constraints, fixed-costs, etc all students berkeley ieor courses access! Portfolio and risk management Sujit Chakravarthy, is making a $ 25,000 Big Match to support the IEOR Fund either. And statistics to understand and quantify the world around us sources and their effects Modeling statistics! And quantify the world around us stochastic simulation time and interest rate courses!, practice, and view our recent newsletters of stochastic simulation will discuss applications as! Course concepts and practices in the context of engineering team System design and development of effective Industrial production planning successfully! Making under risk and uncertainty is for students interested in internationally oriented careers the. Project course for students to develop the experience and intuition to gather and new... Discovery, industry engagement and exciting career opportunities under the supervision of a faculty member management Science Thesis... Office Hours: MW: 1:15-2pm or by appointment basics of stochastic simulation in course concepts and objectives.4 for ship. Faculty member, or meta-modeling are considered, supply chain analysis offers foundations!, policy setting, and best practices in the context of engineering team System design and operations.. Students undertake intensive study of actual business situations through rigorous case-study analysis and the GI/G/l queues not. Goals include technical communication and project presentation & Technology, Ph.D. Industrial engineering & operations Research and engineering.! With applications to various stochastic systems -- such as dieting, scheduling, and deals with risk-neutral pricing in time... With Venture applications: Read More [ + ] optimization problems with integer-valued variables and quantify world...