A deficient grade in INDENG174 may be removed by taking IND ENG 131. With more than 4,000 alumni, 20 faculty, 20 advisory board members and 400 students, the IEOR department is a rapidly growing community equipped with tools and resources to make a large impact in industry, academia, and society. WWW design and queries. Teaching Assistant (GSI): Xingwei Wu, Office Hour: TBD. Risk Modeling, Simulation, and Data Analysis. Supply Chain and Logistics Management: Read More [+], Supply Chain and Logistics Management: Read Less [-], Terms offered: Spring 2014, Fall 2011, Fall 2009 Supply Chain Operation and Management: Read More [+], Supply Chain Operation and Management: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021, Spring 2020 Grading/Final exam status: Letter grade. The result "L = (lambda) w" and other conservation laws. Homeworks and Lab Quizzes: Hardcopies will be . Prerequisites: INDENG165; INDENG173; INDENG172 or STAT134. Credit Restrictions: Students will receive no credit for INDENG174 after completing IND ENG 131. Prerequisites: MATH53, MATH54, and background in Python and programming, Terms offered: Spring 2023, Spring 2022, Spring 2021 The Black-Scholes option-pricing formula will be derived and studied. 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 Search Courses. Algorithms for selected network flow problems. Applications in forecasting and quality control. Students will be exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses. 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. GSI Ahmad Masad 16amasad[at]berkeley.edu Please include [IEOR 130] at the beginning of your subject, e.g. Probability and Risk Analysis for Engineers: the theory, the course covers stochastic simulation techniques that will allow students to go beyond the models and applications discussed in the course. Queueing Theory: Read More [+], Terms offered: Fall 2021, Spring 2018, Spring 2017 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. Join the online learning revolution! Introduction to Financial Engineering: Read More [+], Prerequisites: 162 or 262A, course in probability, or consent of instructor, Introduction to Financial Engineering: Read Less [-], Terms offered: Spring 2023, Fall 2022, Spring 2022 It also discusses applications to queueing theory, risk analysis and reliability theory. Upon completion of the course students will have learned how to: Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. 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. Enrollment restrictions apply. 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. Introductory graduate level course, focusing on applications of operations research techniques, e.g., probability, statistics, and optimization, to financial engineering. Integrate verbal and visual methods of conveying engineering concepts and practices in the classroom and in discussions.5. 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. 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. Describe different mathematical abstractions used in IEOR (e.g., graphs, queues, Markov chains), and how to use these abstractions to model real-world problems. Topics in Risk Theory: Read More [+], Terms offered: Spring 2023, Fall 2022, Spring 2022 Group Studies, Seminars, or Group Research: Read More [+], Fall and/or spring: 15 weeks - 1-4 hours of colloquium per week. 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. The IEOR department plans to offer the following courses in the Spring 2022 semester. 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, with a focus on China. On the other hand, the Master of Analytics focuses on . Fall and/or spring: 15 weeks - 1-3 hours of directed group study per week. Service Operations Design and Analysis: Read More [+], Prerequisites: INDENG162, INDENG173, and a course in statistics, Service Operations Design and Analysis: Read Less [-], Terms offered: Spring 2022, Fall 2021, Spring 2021 IEOR leverages computing to better manage the massive amounts of information available today. 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 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. Stochastic simulation ideas will be introduced and used to obtain the risk-neutral geometric Brownian motion values for certain types of Asian, barrier, and lookback options. Dynamic Production Theory and Planning Models: Read More [+], Dynamic Production Theory and Planning Models: Read Less [-], Terms offered: Spring 2017, Spring 2014, Spring 2011 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. Group Studies, Seminars, or Group Research: Read Less [-], Terms offered: Summer 2023 Second 6 Week Session, Fall 2019, Fall 2016 Grading/Final exam status: Offered for pass/not pass grade only. 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. A Bivariate Introduction to IE and OR: Read More [+]. Supervised group study and research by lower division students. Logistics Network Design and Supply Chain Management: paths, project management and equipment replacement. This course will introduce students to basic statistical techniques such as parameter estimation, hypothesis testing, regression analysis, analysis of variance. Grading/Final exam status: Offered for pass/not pass grade only. Related concepts of computer science tools and theoretical concepts are covered to support the project. 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 A course on financial concepts useful for engineers that will cover, among other topics, those of interest rates, present values, arbitrage, geometric Brownian motion, options pricing, & portfolio optimization. IEOR 166, Decision Analysis IEOR 262A, Mathematical Programming I IEOR 262B, Mathematical Programming II IEOR 190D, Market Engineering and Applications E120, Engineering Economics . Welcome to UC Berkeleys Industrial Engineering and Operations Research Department. Prerequisites: Students should have taken a probability course, such as STAT134 or INDENG172, and should have programming experience in Matlab or Python. understand the array of mathematical toolkits provided by the Python packages covered. On the practical front, supply chain analysis offers solid foundations for strategic positioning, policy setting, and decision making. Prerequisites: IEOR 240 Optimization Analytics, IEOR 241 Risk Modeling & Simulation Analytics, IEOR 242 Applications in Data Analysis. This is an introductory course in stochastic models. Introduction to Machine Learning and Data Analytics: Read More [+]. Flexibility of integer optimization formulations; if-then constraints, fixed-costs, etc. Max-flow min-cut theorem. Please use this as a guide for planning purposes. Supervised Independent Study and Research: Terms offered: Fall 2022, Fall 2021, Fall 2020, Applied Data Science with Venture Applications, Terms offered: Spring 2023, Spring 2022, Fall 2021. , LTI systems, spectral analysis, and frameworks for learning from data. Help us reach our goal Production Systems Analysis: Read More [+], Prerequisites: INDENG160, INDENG173, INDENG162, INDENG165, and ENGIN120, Production Systems Analysis: Read Less [-], Terms offered: Fall 2022, Fall 2021, Fall 2020 Student teams implement an enterprise-scale simulation in a semester-length design project. Students work on a field project under the supervision of a faculty member. Berkeley IEOR MS and PhD Info Session IEOR Graduate Programs Interest Form Apply Now Expand Technical Expertise The Master of Science program will prepare students with the latest theory, computational tools, and research methods through advanced courses in optimization, modeling, simulation, decision analytics, and service operations. Convex optimization as a systematic approximation tool for hard decision problems. Analysis of the capacity and efficiency of production systems. 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. 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. 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) Theory and case studies from a variety of businesses Network Design and Chain! By lower division students systematic approximation tool for hard decision problems berkeley ieor courses and visual methods of conveying concepts... Exposed to the key concepts through a mixture of foundational theory and case studies from a variety of businesses integer!: Offered for pass/not pass grade only teaching Assistant ( GSI ): Xingwei Wu, Office:... The classroom and in discussions.5 Wu, Office Hour: TBD Supply Chain analysis offers foundations. 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