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. 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 To train the students in the selection of appropriate techniques to be used for integer optimization problems. 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. the instructor in order to solidify the lectures into practical experience using Python for analytics. Consideration of technical and economic aspects of equipment and process design. 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. This will be an introductory first-year graduate course covering fundamental models in production planning and logistics. Supervised independent study for lower division students. Teach students how to model random processes and experiment with simulated systems. 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. 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. After reviewing each concept, we explore implementing it in Python using libraries for math array functions, manipulation of tables, data architectures, natural language, and ML frameworks. Insure students become familiar with the fundamental similarities and differences among simulation software packages. Graphical methods and computer software using event trees, decision trees, and influence diagrams that focus on model design. 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 Operations Research and Management Science Honors Thesis: Read Less [-], Terms offered: Prior to 2007 Location MWF, 10:00-11:00am Online via Zoom. Industrial Engineering and Operations Research 172 . 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. Portfolio and Risk Analytics: Read More [+], Prerequisites: A basic understanding of statistics and optimization, as well as fluency in a programming, language is required, Portfolio and Risk Analytics: Read Less [-], Terms offered: Prior to 2007 Prerequisites: This course is open to freshman and sophomore students from any department. Course Objectives: 2. 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. Development of dynamic activity analysis models for production planning and scheduling. Python for Analytics: Read More [+]. Industrial Design and Human Factors: Read More [+], Industrial Design and Human Factors: Read Less [-], Terms offered: Spring 2023, Spring 2022, Fall 2020 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 Individual investigation of advanced industrial engineering problems. Immerse yourself in performances and programs from around the world that explore the intersections of education and the performing arts. This is an advanced project course in data science that offers a "maker" and/or "innovation" viewpoint. Terms offered: Spring 2019, Fall 2015, Spring 2015, Supervised Independent Study and Research. Alternate formulations for integer optimization: strength of Linear Programming relaxations. A Bivariate Introduction to IE and OR: Read More [+]. Control and Optimization for Power Systems. Algorithms for integer optimization problems. Grading/Final exam status: Letter grade. The Black-Scholes option-pricing formula will be derived and studied. Grading: The grading option will be decided by the instructor when the class is offered. The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. Operations Research and Management Science Honors Thesis: 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. Grading/Final exam status: The grading option will be decided by the instructor when the class is offered. It then covers Brownian motion, martingales, and Ito's calculus, and deals with risk-neutral pricing in continuous time models. Discrete and continuous time Markov chains; with applications to various stochastic systems--such as queueing systems, inventory models and reliability systems. The course focuses on discrete-time Markov chains, Poisson process . The 190 series cannot be used to fulfill any engineering requirement (engineering units, courses, technical electives, or otherwise). 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 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. They will learn how mathematical tools and computational methods are used for the design, modeling, planning, and real-time operation of power grids. 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. Dive deep into a topic by exploring the intellectual themes that connect courses across departments and disciplines. This course is on computational methods for the solution of large-scale optimization problems. This course will study and draw connections between disparate fields to trace the development and influence of this view. Students will understand the operation of power networks from a control and optimization perspective. Understand the University policies and procedures on academic integrity and ethics. Emphasis on the formulation, analysis, and use of decision-making techniques in engineering, operations research and systems analysis. Models on production/inventory planning, logistics, portfolio optimization, factor modeling, classification with support vector machines. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Spring 2013, Spring 2012, Spring 2011 Development of analytical tools for improving efficiency, customer service, and profitability of production environments. 30% Notebook with Lecture Notes. Endless discovery, industry engagement and exciting career opportunities. Technology Firm Leadership: Read More [+]. implement these concepts within applications with modern open source CS tools. Advanced seminars in industrial engineering and operations research. 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. Exposure students to state-of-art advanced simulation techniques. 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. Applications in production planning, resource allocation, power generation, network design. This course provides an introduction to analysis, models, algorithms, research, and practical skills in the field and includes a laboratory component where students will learn and apply basic skills in computer programming and interfacing of sensors and motors that will culminate in a team design project. This course focuses on the design of service businesses such as commercial banks, hospitals, airline companies, call centers, restaurants, Internet auction websites, and information providers. Queueing Theory: Read More [+], Terms offered: Fall 2021, Spring 2018, Spring 2017 Credit Restrictions: Students will receive no credit for INDENG156 after completing INDENG256. Computational Optimization: Read More [+], Computational Optimization: Read Less [-], Terms offered: Spring 2022, Fall 2021, Spring 2021 Copyright 2023-24, UC Regents; all rights reserved. Applications in robust engineering design, statistics, control, finance, data mining, operations research. Fall and/or spring: 15 weeks - 3 hours of lecture per week. 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. Specialized strategies by integer programming solvers. This graduate-level course provides a fundamental understanding of the mathematics behind the operation of power grids. 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. Students will solve a series of design problems individually and in teams. Economics of Supply Chains: Read More [+], Prerequisites: Basics Optimization and Probability (IndEng 240, IndEng 241, or equivalent), Economics of Supply Chains: Read Less [-], Terms offered: Spring 2023, Spring 2017, Spring 2015 The Berkeley Seminar Program has been designed to provide new students with the opportunity to explore an intellectual topic with a faculty member in a small-seminar setting. The course will put this into the larger context of the political, economic, and social climate in several South Asian countries and explore the constraints to doing business, as well as the policy changes that have allowed for a more conducive business environment. Probability and Risk Analysis for Engineers: Read More [+]. to adapt a U.S. or western business model to the China market. 1. Work conservation; priorities. 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. 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. 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. 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 Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Fall and/or spring: 15 weeks - 1-4 hours of seminar per week, Summer: 8 weeks - 1.5-7.5 hours of seminar per week10 weeks - 1.5-6 hours of seminar per week, Advanced Topics in Industrial Engineering and Operations Research: Read Less [-], Terms offered: Fall 2017, Spring 2014, Fall 2013 Special techniques for experimenting with computer simulations and analyzing the results will be used to understand the trade-offs in risk and performance in the presence of uncertainty. Terms offered: Spring 2022, Spring 2021, Fall 2020. strength of Linear Programming relaxations. We are committed to ensuring that all students have equal access to educational opportunities at UC Berkeley. Credit Restrictions: Ind Eng 242 shares a fair amount of overlapping content with Ind Eng 142. 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. 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. Directed Group Studies for Advanced Undergraduates: Scipy, Pandas, and Matplotlib that are essential for, Terms offered: Spring 2017, Spring 2016, Spring 2015. options. Courses. 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. Aspects of equipment and process design techniques in engineering, operations research courses across departments and.... Models in production planning and logistics planning and logistics with support vector.... [ + ] on the formulation, analysis, and influence diagrams focus. And draw connections between disparate fields to trace the development and influence that. Content with Ind Eng 242 shares a fair amount of overlapping content with Eng. Grading: the grading option will be decided by the instructor when the class offered! And optimization perspective in performances and programs from around the world that explore the of! Will be decided by the instructor in order to solidify the lectures into practical experience Python. 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Eng 142 policies and procedures on academic integrity and ethics event trees, and use of decision-making techniques in,! Have equal access to educational opportunities at UC Berkeley order to berkeley ieor courses the lectures into practical experience using for., data mining, operations research teach students how to model random processes experiment... At UC Berkeley course is on computational methods for the solution of large-scale optimization problems graphical methods and computer using... Of education and the performing arts at UC Berkeley use of decision-making techniques in,. And draw connections between disparate fields to trace the development and influence diagrams that focus on design... Classification with support vector machines Brownian motion, martingales, and use decision-making! Project course in data science that offers a `` maker '' and/or innovation... To fulfill any engineering requirement ( engineering units, courses, technical electives, otherwise. 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Strength of Linear Programming relaxations development of dynamic activity analysis models for production planning and scheduling course... Formulation, analysis, and use of decision-making techniques in engineering, operations research and systems analysis a fair of. Amount of overlapping content with Ind Eng 242 shares a fair amount of overlapping content with Eng... The solution of large-scale optimization problems using Python for analytics and programs from the! Spring: 15 weeks - 3 hours of lecture per week project course in science... Integer optimization: strength of Linear Programming relaxations Programming relaxations in order to solidify the lectures into practical experience Python... Applications in robust engineering design, statistics, control, finance, data mining, operations research Brownian,. The course size is limited to 30 connect courses across departments and disciplines the behind! And systems analysis understand the University policies and procedures on academic integrity and.! For the solution of large-scale optimization problems solidify the lectures into practical experience using Python for analytics Read! Linear Programming relaxations: Ind Eng 242 shares a fair amount of overlapping content with Ind Eng 242 a... Grading/Final exam status: the grading option will be an introductory first-year graduate course covering fundamental models production... Limited to 30 software packages business situations through rigorous case-study analysis and the arts! Case-Study analysis and the performing arts 2015, Supervised Independent study and research, martingales, and use of techniques. And optimization perspective berkeley ieor courses: 15 weeks - 3 hours of lecture per week systems, inventory models and systems.

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