Brief introduction to decision making under risk and uncertainty. Berkeley Seminars are offered in all campus departments, and topics vary from department to department and semester to semester. The main goal is to develop proficiency in common optimization modeling languages, and learn how to integrate them with underlying optimization solvers. Industrial Engineering and Operations Research 172 . descriptive, predictive, and prescriptive analytics. IEOR improves processes to create a better world. Simulation for Enterprise-Scale Systems: Read More [+]. Student teams implement an enterprise-scale simulation in a semester-length design project. Probabilitybackgroundwith Industrial Engineering173 orequivalentisrecommended, Applied Stochastic Process I: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 Students will work on group projects along with Industrial Engineering and Operations Research (IEOR) Dept University of California at Berkeley Lectures and Labs: MW 5-6:30, 3106 Etcheverry Hall Web Page: www.ieor.berkeley.edu/~ieor170 3 Credits. Integer Programming and Combinatorial Optimization: Read More [+], Integer Programming and Combinatorial Optimization: Read Less [-], Terms offered: Fall 2015, Fall 2014 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. 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. Convex sets and convex functions; local optimality; KKT conditions; Lagrangian duality; steepest descent and Newton's method. Course Objectives: Introductory course on the theory and applications of decision analysis. Discussion, practice, and review of fundamentals, issues, and best practices in teaching for any engineering course. Faculty research in Berkeley IEOR specializes in stochastic processes, optimization, and supply chain management. To acquire skills in the best modeling approach that is suitable to the practical problem at hand. Credit Restrictions: Course may be repeated for a maximum of four units per semester. Network Flows and Graphs: Read More [+], Prerequisites: 262A (may be taken concurrently), Terms offered: Spring 2022, Spring 2016, Spring 2015 Search Courses. Applied Data Science with Venture Applications: Introduction to Machine Learning and Data Analytics, Terms offered: Spring 2023, Fall 2022, Spring 2022. 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. Techniques for yield analysis, process control, inspection sampling, equipment efficiency analysis, cycle time reduction, and on-time delivery improvement. IEOR utilizes math and statistics to understand and quantify the world around us. 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Through a series of real-world examples, students will learn to identify opportunities to leverage the capabilities of data analytics and will see how data analytics can provide a competitive edge for companies.4. Simulation for Enterprise-Scale Systems: Read Less [-], Terms offered: Spring 2023, Spring 2022, Spring 2021 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 Group studies of selected topics. Student Learning Outcomes: Learning goals include technical communication and project presentation. 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. 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