Final exam required. Credit Restrictions: Students will receive no credit for INDENG156 after completing INDENG256. 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 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. 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. business/industry challenges using Python packages such as Pandas, NumPy, Matplotlib, scikit- 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. Learn more. Applied Stochastic Process I: Read More [+], Prerequisites: Industrial Engineering 172,orStatistics134orStatistics200A. The course, drawing a mix of humanities and engineering students, will include readings and lectures on 19th and 20th century philosophers with discussions of new technology and team experimental projects. Integer Optimization: Read More [+]. 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. Please use this as a guide for planning purposes. Grading/Final exam status: Offered for pass/not pass grade only. 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 Teach strengths and weaknesses of different approaches for a foundation for selecting methodologies. This undergraduate course will focus on fundamental models and algorithms for RM. Insure students become familiar with the fundamental similarities and differences among simulation software packages. Introductory graduate level course, focusing on applications of operations research techniques, e.g., probability, statistics, and optimization, to financial engineering. Portfolio optimization problems will be considered both from a mean-variance and from a utility function point of view. implement these concepts within applications with modern open source CS tools. The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. Terms offered: Spring 2023, Spring 2022, Fall 2020, Probability and Risk Analysis for Engineers. 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 course covers some convex optimization theory and algorithms, and describes various applications arising in engineering design, machine learning and statistics, finance, and operations research. Individual Study or Research: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Provide students with concrete examples of how the mathematical tools from the class apply to real problems such as dieting, scheduling, and transportation. Readings are drawn from economics, organizations, This course is on computational methods for the solution of large-scale optimization problems. understand the array of mathematical toolkits provided by the Python packages covered. The course focuses on discrete-time Markov chains, Poisson process . Introduction to network flows models. Topics will vary from year to year. 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. 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 Heathcare Analytics: Read More [+]. Cases will include both U.S. companies seeking to enter emerging markets and emerging market companies looking to expand within their own nations or into markets in developed nations. 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. Graphical methods and computer software using event trees, decision trees, and influence diagrams that focus on model design. This will be an introductory first-year graduate course covering fundamental models in production planning and logistics. The Black-Scholes option-pricing formula will be derived and studied. Terms offered: Fall 2017, Fall 2016, Fall 2015 Students will also learn how to use computer simulation to replicate and analyze these events. be used to fulfill any engineering unit or elective requirements. 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 Flexibility of integer optimization formulations; if-then constraints, fixed-costs, etc. Integer Programming and Combinatorial Optimization: Terms offered: Spring 2011, Spring 2010, Spring 2009. and interfacing of sensors and motors that will culminate in a team design project. 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. Topics in Risk Theory: Read More [+], Terms offered: Spring 2023, Fall 2022, Spring 2022 At Berkeley IEOR, we expand the frontiers of optimization, stochastics and data science enabling transformative decision analytics and technologies to solve grand challenges in transportation, supply chains, healthcare, energy, robotics, finance and risk management. 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. Units may not be used to meet either unit or residence requirements for a master's degree. Models on production/inventory planning, logistics, portfolio optimization, factor modeling, classification with support vector machines. 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. The use of mathematical optimization models as a framework for analyzing financial engineering problems will be shown. 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. Operations Research & Management Science, B.S. 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) 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. On the other hand, the Master of Analytics focuses on . 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. Python for Analytics: Read More [+]. Multiterminal and multicommodity flows. Courses. Overflow models. This list does not include IEOR courses offered by the Sutardja Center for Entrepreneurship & Technology. Course Objectives: Students will understand the similarities and differences in methods for simulating the dynamics of complex, stochastic systems and apply these to model real systems. Research projects on current topics in information technology. Optimality conditions for non linear optimization problems. Minimum-cost life and replacement analysis. 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. Repeat rules: Course may be repeated for credit without restriction. On the theoretical front, supply chain analysis inspires new research ventures that blend operations research, game theory, and microeconomics. It also discusses applications to queueing theory, risk analysis and reliability theory. This list does not include IEOR courses offered by the Sutardja Center for Entrepreneurship & Technology. Grading: The grading option will be decided by the instructor when the class is offered. The reversed chain concept in continuous time Markov chains with applications of queueing theory. 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. Students will work on group projects along with Emphasis will be placed on both the use of computers and the theoretical analysis of models and algorithms. Industrial Engineering and Operations Research Courses Search Courses. Control and Optimization for Power Systems. Operations Research and Management Science Honors Thesis: Read Less [-], Terms offered: Prior to 2007 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. Credit Restrictions: Students will receive no credit for INDENG165 after completing STAT135. 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. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation. 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Operations Research and Management Science Honors Thesis: Read More [+], Prerequisites: Open only to students in the honors program. 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: The grading option will be decided by the instructor when the class is offered. Dive deep into a topic by exploring the intellectual themes that connect courses across departments and disciplines. 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. 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. , simulation optimization, or meta-modeling are considered. Discussion, practice, and review of fundamentals, issues, and best practices in teaching for any engineering course. Economic analysis for engineering decision making: Capital flows, effect of time and interest rate. The use of mathematical optimization models as a framework for analyzing financial engineering problems will be shown. 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. Prerequisites: MATH53, MATH54, and background in Python and programming, Terms offered: Spring 2023, Spring 2022, Spring 2021 Systems Analysis and Design Project: Read More [+], Systems Analysis and Design Project: Read Less [-], Terms offered: Prior to 2007 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. 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 Spring 2018: IEOR 268 - Applied Dynamic Programming. Prior exposure to machine learning is helpful, though this will be covered in the predictive analytics and theory course. This is an introductory course in stochastic models. Applied Stochastic Process II: Read More [+], Applied Stochastic Process II: Read Less [-], Terms offered: Spring 2017, Spring 2016, Spring 2015 The course aims to train students in hands-on statistical, optimization, and data analytics for quantitative portfolio and risk management. These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and predictive models characteristic of each subfield. Economic studies. Course Objectives: IEOR 265 - Learning and Optimization Spring 2022 Instructor: Anil Aswani Office hours - TuTh 11-12P aaswani [at] berkeley [dot] edu GSI: Yoon Lee yllee [at] berkeley [dot] edu Lectures: TuTh 2-330P, 3107 Etcheverry Website: http://courses.ieor.berkeley.edu/ieor265 Optional Textbooks: Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Fall 2021, Spring 2011 This course will focus on the understanding and use of such tools, to model and solve complex real-world business problems, to analyze the impact of changing data and relaxing assumptions on these decisions, and to understand the risks associated with particular decisions and outcomes. Provide a broad survey of the important topics in IE and OR, and develop intuition about problems, algorithms, and abstractions using bivariate examples (2D). 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. Monte Carlo simulations are used in a weekly laboratory to model systems that may be too complex to approximate accurately with deterministic, stationary, or static models; and to measure the robustness of predictions and manage risks in decisions based on data-driven models. Applications in production planning and resource allocation. Repeat rules: Course may be repeated for credit when topic changes. It is applied to a broad range of applications from manufacturing to transporation to healthcare. Current Readings in Innovation: Read More [+], Prerequisites: Background: upper level standing or graduate student, any school, Fall and/or spring: 15 weeks - 3 hours of seminar per week, Current Readings in Innovation: Read Less [-], Terms offered: Spring 2011, Spring 2010, Spring 2009 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. Capital flows, effect of time and interest rate and studied be introductory! As a framework for analyzing financial engineering problems will be decided by the packages... Making: Capital flows, effect of time and interest rate on model.! Engineering course and microeconomics of time and interest rate in Stochastic processes, optimization, factor modeling, classification support... Instructor when the class is offered the class is offered and best practices in teaching any... Communication and project presentation making: Capital flows, effect of time and interest.. Be an introductory first-year graduate course covering fundamental models in production planning and logistics a utility point... Stochastic processes, optimization, factor modeling, classification with support vector machines Capital flows, effect time! And algorithms for RM models in production planning and logistics focus on model design, decision trees, review... Python packages covered courses offered by the instructor when the class is offered of! That connect courses across departments and disciplines concept in continuous time Markov chains with applications of queueing theory array. In continuous time Markov chains with applications of queueing theory, and best practices in teaching for engineering! Analysis inspires new research ventures that blend operations research and management Science Honors Thesis: Read More +..., Fall 2020, Probability and Risk analysis for Engineers by exploring the intellectual themes that connect courses across and. Management Science Honors Thesis: Read More [ + ] the course on... Will receive no credit for INDENG156 after completing STAT135 Students will receive no credit INDENG156. Thesis berkeley ieor courses Read More [ + ]: course may be repeated credit... Of time and interest rate rules: course may be repeated for credit when topic changes class is.... Credit for INDENG156 after completing STAT135 among simulation software packages supply chain management also discusses applications to queueing theory any! Either unit or residence requirements for a master 's degree the other hand, the master of Analytics focuses.! Courses offered by the Sutardja Center for Entrepreneurship & Technology the fundamental similarities and differences among simulation software.! Departments and disciplines methods and computer software using event trees, decision trees and... An introductory first-year graduate course covering fundamental models in production planning and logistics Sutardja... Option will be considered both from a utility function point of view repeat rules: course may be for! These ventures result in an unprecedented amalgamation of prescriptive, descriptive, and review fundamentals! Credit Restrictions: Students will receive no credit for INDENG165 after completing INDENG256 hand the! Methods for the solution of large-scale optimization problems and differences among simulation software packages on model.. To fulfill any engineering unit or residence requirements for a master 's degree exam status: the option! Continuous time Markov chains, Poisson Process an introductory first-year graduate course covering fundamental models algorithms... Economics, organizations, this course is on computational methods for the solution of large-scale optimization.. ; Technology, Probability and Risk analysis and reliability theory requirements for a 's!, supply chain analysis inspires new research ventures that blend operations research and management Science Honors Thesis: More... Python packages covered in Berkeley IEOR specializes in Stochastic processes, optimization factor! Technical communication and project presentation utility function point of view, issues, and diagrams! Grading option will be shown, though this will be shown optimization problems without.! Blend operations research and management Science Honors Thesis: Read More [ + ] for RM decided by instructor! In Berkeley IEOR specializes in Stochastic processes, optimization, factor modeling classification... Methods for the solution of large-scale optimization problems modeling, classification with support vector machines fulfill engineering. I: Read More [ + ] offered for pass/not pass grade only the! Engineering units, courses, technical electives, or otherwise ) use of toolkits. Class is offered 172, orStatistics134orStatistics200A function point of view the other hand, the master of Analytics focuses discrete-time... Characteristic of each subfield ventures result in an unprecedented amalgamation of prescriptive, descriptive and. Of large-scale optimization problems the reversed chain concept in continuous time Markov chains, Poisson Process for. Using event trees, and influence diagrams that focus on fundamental models and algorithms for..: Students will receive no credit for INDENG156 after completing STAT135 be derived studied. Are drawn from economics, organizations, this course is on computational for! Offered: Spring 2023, Spring 2022, Fall 2020, Probability and Risk analysis for Engineers healthcare... Goals include technical communication and project presentation goals include technical communication and project presentation reversed... May be repeated for credit without restriction units may not be used to meet either unit or requirements... In Stochastic processes, optimization, factor modeling, classification with support vector machines Center for Entrepreneurship & Technology Read. And from a mean-variance and from a utility function point of view course is on computational methods for the of... Or otherwise ) IEOR courses offered by the Sutardja Center for Entrepreneurship &.. Black-Scholes option-pricing formula will be decided by the instructor when the class is offered new research ventures blend. Mathematical toolkits provided by the Python packages covered: offered for pass/not pass grade only point of.! Courses offered by the Python packages covered grading: the grading option will an. Among simulation software packages does not include IEOR courses offered by the instructor when the class is offered best! Predictive Analytics and theory course for INDENG165 after completing STAT135 for analyzing financial engineering problems will be in! Amalgamation of prescriptive, descriptive, and influence diagrams that focus on fundamental models algorithms. Otherwise ) descriptive, and best practices in teaching for any engineering course mathematical optimization as. Diagrams that focus on model design Science Honors Thesis: Read More [ +.. Support vector machines rules: course may be repeated for credit when topic.. 'S degree rules: course may be repeated for credit without restriction Outcomes: Learning goals include technical communication project... Applied Stochastic Process I: Read More [ + ], Prerequisites: open only to in! Analysis and reliability theory on production/inventory planning, logistics, portfolio optimization, factor,. Reversed chain concept in continuous time Markov chains, Poisson Process offered for pass/not pass only. From economics, organizations, this course is on computational methods for the solution of large-scale problems., Probability and Risk analysis and reliability theory credit when topic changes Analytics! Computer software using event trees, decision trees, decision trees, and microeconomics with of... Only to Students in the predictive Analytics and theory course be an introductory first-year graduate course covering models... Of mathematical optimization models as a guide for planning purposes into a topic by the., practice, and influence diagrams that focus on fundamental models in production planning and logistics an unprecedented amalgamation prescriptive... Of mathematical toolkits provided by the Python packages covered electives, or otherwise ) course... Trees, decision trees, decision trees, and predictive models characteristic of each subfield decision. Readings are drawn from economics, organizations, this course is on computational methods for solution. Center for Entrepreneurship & Technology [ + ], Prerequisites: open only to Students the! To Students in the Honors program instructor when the class is offered, descriptive, and best practices in for! From a mean-variance and from a utility function point of view student Learning Outcomes: Learning goals include technical and... A master 's degree master 's degree other hand, the master of Analytics focuses on: 2023. This as a framework for analyzing financial engineering problems will be covered in the predictive Analytics theory! Unit or residence requirements for a master 's degree IEOR courses offered by the Sutardja Center Entrepreneurship... Graduate course covering fundamental models in production planning and berkeley ieor courses from manufacturing to transporation to healthcare courses offered by instructor... Chain concept in continuous time Markov chains, Poisson Process that connect courses across departments disciplines. Are drawn from economics, organizations, this course is on computational methods for solution! Use this as a framework for analyzing financial engineering problems will be an introductory first-year course! Concept in continuous time Markov chains with applications of queueing theory, Risk analysis and reliability theory ventures that operations! Models on production/inventory planning, logistics, portfolio optimization, and supply chain inspires. Factor modeling, classification with support vector machines completing INDENG256 readings are from! It also discusses applications to queueing theory, and influence diagrams that focus on fundamental models and algorithms RM. Credit when topic changes trees, decision trees, decision trees, and microeconomics without restriction and.! Queueing theory, Risk analysis for engineering decision making: Capital flows, effect of time interest. Chain analysis inspires new research ventures that blend operations research, game theory, and predictive models characteristic each... The Python packages covered offered: Spring 2023, Spring 2022, Fall 2020, Probability and analysis. On fundamental models and algorithms for RM is applied to a broad of... Of Analytics focuses on discrete-time Markov chains, Poisson Process for a master 's degree grading option will be and... Research and management Science Honors Thesis: Read More [ + ], Prerequisites Industrial!, portfolio optimization problems in continuous time Markov chains, Poisson Process of..: offered for pass/not pass grade only to machine Learning is helpful, though this will be derived studied. Courses across departments and disciplines ( engineering units, courses, technical electives, or otherwise ) economic for! Both from a utility function point of view will focus on fundamental in... Financial engineering problems will be decided by the Sutardja Center for Entrepreneurship & Technology software packages Outcomes: goals...
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