exploratory analytics to systems analytics in an industry context, including communication of The main goal is to develop proficiency in common optimization modeling languages, and learn how to integrate them with underlying optimization solvers. 30% Notebook with Lecture Notes. Understand the University policies and procedures on academic integrity and ethics. 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. Provide a broad survey of the important topics in IE and OR, and develop intuition about problems, algorithms, and abstractions using bivariate examples (2D). Familiarity with the Python programming language is also expected, Terms offered: Fall 2013 In this award-winning video, IEOR students explain what industrial engineering & operations research is, how their skills can improve the world, and discuss exciting careers in IEOR. Applications will be given in such areas as reliability theory, risk theory, inventory theory, financial models, and computer science, among others. Fall and/or spring: 15 weeks - 3 hours of lecture per week. Students will gain experience with a commercial database management system and will work in teams with Overflow models. We focus on the relational database model and learn the mathematics of structured queries. recommendations. Students undertake intensive study of actual business situations through rigorous case-study analysis. Through art and film programs, collections and research resources, BAM/PFA is the visual arts center of UC Berkeley. Credit Restrictions: Course may be repeated for credit with consent of instructor. 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. Enable the students to recognize when problems can be modeled as integer optimization problems. A project course to provide hands-on experience in end-to-end analytics development from 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. Innovations that we will discuss include collaborative forecasting, social media, online procurement, and technologies such as RFID. The use of mathematical optimization models as a framework for analyzing financial engineering problems will be shown. 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. The PDF will include all information unique to this page. 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 Conditional Expectation. 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. Advanced seminars in industrial engineering and operations research. Applied Data Science with Venture Applications: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 Emphasis on the formulation, analysis, and use of decision-making techniques in engineering, operations research and systems analysis. Homeworks and Lab Quizzes: Hardcopies will be . Explore the Arts Research Center at UC Berkeley a think tank for the arts and a genuinely interdisciplinary space. 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 To introduce students to the core concepts of optimization Standard topics include Girsanov transformation, martingale representation theorem, Feyman-Kac formula, and American and exotic option pricings. develop custom Python scripts and functions to perform analytic computations; Supervised Independent Study and Research: Read More [+], Prerequisites: Freshman or sophomore standing and consent of instructor, Fall and/or spring: 15 weeks - 1-4 hours of independent study per week, Summer: 8 weeks - 1.5-7.5 hours of independent study per week10 weeks - 1.5-6 hours of independent study per week, Supervised Independent Study and Research: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Course Objectives: 1. Dynamic programming formulation of deterministic decision process problems, analytical and computational methods of solution, application to problems of equipment replacement, resource allocation, scheduling, search and routing. IEOR leverages computing to better manage the massive amounts of information available today. Degree Programs Industrial Engineering and Operations Research Industrial Engineering and Operations Research About the Program Bachelor of Science (BS) The Bachelor of Science (BS) degree in Industrial Engineering and Operations Research (IEOR) is designed to prepare students for technical careers in production or service industries. The course is They will also manage hypothetical portfolios throughout the course. Research projects on current topics in information technology. Applications in forecasting and quality control. In this course, students will learn essential Product Management skills by putting theory into practice, on a product or idea of your choosing. Special Topics in Industrial Engineering and Operation Research: Dynamic Production Theory and Planning Models, Terms offered: Spring 2014, Fall 2008, Spring 2008. Modelling principles are illustrated by reviewing actual large-scale planning systems successfully implemented for naval ship overhaul and for semiconductor manufacturing. 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. Deadline Friday, January 6, 2023, 8:59 pm PST FAQ Concentrations Management Science & Engineering FinTech 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 The emphasis will be on computational methods such as variants of GARCH, Black-Litterman, conic optimization, Monte Carlo simulation for risk and optimization, factor modeling. 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 Alternative to final exam. 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. Familiarize students in leading methodologies for solving integer optimization problems, and techniques in these methodologies. Fall 2017: IEOR 160 - Nonlinear and Discrete Optimization. Analysis and Design of Databases: Read More [+], Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week, Analysis and Design of Databases: Read Less [-], Terms offered: Spring 2017, Spring 2016, Spring 2015 Introduce students to modern techniques for developing computer simulations of stochastic discrete-event models and experimenting with such models to better design and operate dynamic systems. Learn more about our game-changing alumni, and view our recent newsletters. 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. To train the students in the selection of appropriate techniques to be used for integer optimization problems. Advanced topics in information management, focusing on design of relational databases, querying, and normalization. In addition, the course will introduce elements of financial markets and asset classes. Graphical methods and computer software using event trees, decision trees, and influence diagrams that focus on model design. Supervised group study and research by lower division students. Credit Restrictions: Course restricted to Freshman students. Different methods of evaluation of alternatives. Help us reach our goal Readings are drawn from economics, organizations, This seminar and discussion class aims to survey current and classic research on innovation and help Industrial Engineering and Operations Research Courses Search Courses. IEOR improves processes to create a better world. Duality theory. Grading/Final exam status: The grading option will be decided by the instructor when the class is offered. This course is ideal for students who have taken COMPSCIC8 / DATAC8 / INFOC8 / STATC8. Linear Programming and Network Flows: Read More [+], Linear Programming and Network Flows: Read Less [-], Terms offered: Spring 2023 Spring 2017: IEOR 268 - Applied Dynamic Programming. 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. Industrial Engineering and Operations Research142 Introduction to Machine Learning and Data Analytics Search Courses Exams Instructors Type Term Exam Solution Flag (E) Flag (S) Grigas Midterm 1 Fall 2019 Solution Flag Syllabi Instructors Term Download Flag Grigas Fall 2019 Download Flag Home| Contact Us Convex optimization as a systematic approximation tool for hard decision problems. Summer: 6 weeks - 2.5-10 hours of independent study per week8 weeks - 2-7.5 hours of independent study per week10 weeks - 1.5-6 hours of independent study per week, Supervised Independent Study: Read Less [-], Terms offered: Prior to 2007 This undergraduate course will focus on fundamental models and algorithms for RM. Grading/Final exam status: Offered for pass/not pass grade only. to adapt a U.S. or western business model to the China market. Portfolio optimization problems will be considered both from a mean-variance and from a utility function point of view. Basic first year graduate course in optimization of non-linear programs. Lectures and appropriate assignments on fundamental or applied topics of current interest in industrial engineering and operations research. Applications in robust engineering design, statistics, control, finance, data mining, operations research. Welcome to UC Berkeleys Industrial Engineering and Operations Research Department. Simulation techniques will be discussed at the end of the semester, and MATLAB (or C or S-Plus) will be used for computation. Operations Research and Management Science Honors Thesis: Read Less [-], Terms offered: Prior to 2007 The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. Risk Modeling, Simulation, and Data Analysis: Supply Chain Innovation, Strategy, and Analytics. Operations Research and Management Science Honors Thesis: Read More [+], Prerequisites: Open only to students in the honors program. Location MWF, 10:00-11:00am Online via Zoom. Introduction to Stochastic Processes: Read More [+]. Operations Research and Management Science Honors Thesis: Read More [+], Terms offered: Spring 2023, Fall 2022, Spring 2022 Freshman Seminars: Read More [+]. Control and Optimization for Power Systems. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Spring 2017, Fall 2014, Spring 2014 Terms offered: Spring 2023, Fall 2022, Spring 2022 Special Topics in Industrial Engineering and Operation Research: Read More [+], Prerequisites: Upper level standing or graduate student, Fall and/or spring: 15 weeks - 2-3 hours of lecture per week, Summer: 6 weeks - 5-7.5 hours of lecture per week10 weeks - 3-4.5 hours of lecture per week, Special Topics in Industrial Engineering and Operation Research: Read Less [-], Terms offered: Spring 2014, Fall 2008, Spring 2008 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. Engineering Statistics, Quality Control, and Forecasting: Terms offered: Spring 2022, Spring 2021, Fall 2019. trees, and influence diagrams that focus on model design. Terms offered: Spring 2022, Spring 2021, Spring 2020, Spring 2019, Spring 2018, Spring 2017. , control, finance, data mining, operations research. The course will start with a quick review of 222: the basics of Brownian motion, martingales, Ito's calculus, risk-neutral pricing in continuous time models. Dive deep into a topic by exploring the intellectual themes that connect courses across departments and disciplines. 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. Related concepts of computer science tools and theoretical concepts are covered to support the project. Instructors Type Term Exam Solution Flag (E) Flag (S) Shanthikumar All courses are subject to change. Advanced Topics in Industrial Engineering and Operations Research: Read More [+], Terms offered: Fall 2021, Spring 2011 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 Student teams implement an enterprise-scale simulation in a semester-length design project. Design and implementation of databases, with an emphasis on industrial and commercial applications. 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 [+] The course is focused around intensive study of actual business situations through rigorous case-study analysis and the course size is limited to 30. Prerequisites: INDENG165; INDENG173; INDENG172 or STAT134. Credit Restrictions: Students will receive no credit for INDENG174 after completing IND ENG 131. Integer Optimization: Read More [+]. Applied Stochastic Process II: Read More [+], Applied Stochastic Process II: Read Less [-], Terms offered: Spring 2017, Spring 2016, Spring 2015 The course content exposes students interested in internationally oriented careers to the strategic thinking involved in international engagement and expansion. 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. Undergraduate Field Research in Industrial Engineering: Directed Group Studies for Advanced Undergraduates. 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 Simulation for Enterprise-Scale Systems: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 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. Includes formulation of risk problems and probabilistic risk assessments. To complement the theory, the course also covers the basics of stochastic simulation. 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. Prior exposure to machine learning is helpful, though this will be covered in the predictive analytics and theory course. Introductory graduate level course, focusing on applications of operations research techniques, e.g., probability, statistics, and optimization, to financial engineering. 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. 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. Final exam required. Introduce students to the data analysis process including: developing a hypothesis, acquiring data, processing the data, testing the hypothesis, and presenting results. This course is on computational methods for the solution of large-scale optimization problems. Design and development of effective industrial production planning systems. This course is designed primarily for upper-level undergraduate and graduate students interested in examining the major challenges and success factors entrepreneurs and innovators face in conducting business, globalizing a company product or service, or investing in South Asia. They will also manage hypothetical portfolios throughout the course. Teach strengths and weaknesses of different approaches for a foundation for selecting methodologies. 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berkeley ieor courses