Introduction to investment and financial instruments via portfolio theory and derivative securities, using basic operations research/engineering methodology. Introduction to quantitative modeling of credit risk, with a focus on the pricing of credit derivatives. Aims to develop and harness the modeling, analytical, and managerial skills of engineering students and apply them to improve the operations of both service and manufacturing firms. For students who have not studied linear programming. Analytical models, flow models of service networks, Littles law, measuring methods in face-to-face and computerized systems, forecasting methods, stability of service systems, operational quality of service, economies of scale, staffing, complex service networks, skill-based routing. IEORE4743Financial Correlations Modeling, Trading, Risk Management AI. Selected topics of special interest to M.S. Application of various computational methods/techniques in quantitative/computational finance. IEORE4522PYTHON FOR OPERATIONS RESEARCH. A specialized version of IEORE4150 for MSE and MSBA students who are exempt from the first half of IEORE4101. Course Topics including: Python Crash Course Requests (GET/POST), json, xml Web Scraping via BeautifulSoup Numpy & Pandas Data Visualizations via matplotlib and seaborn Text Mining, Twitter API and Yelp API Network Analysis Prerequisites: (IEORE4706) and (IEORE4707) and computer programming. An introductory course in graph theory with emphasis on its combinatorial aspects. Prerequisites: (IEORE4706) and (IEORE4707), Prerequisites: (IEORE4701) and (IEORE4707). Selected topics of interest in the area of quantitative finance. IEOR Course Notes for Columbia University Students | Uloop IEORE4734FOR EXCH/RELATD DERIVATVS INST. Prerequisite(s): IEORE4700. 3.00 points. Introduces risk management principles, practical implementation and applications, standard market, liquidity, and credit risk measurement techniques, and their drawbacks and limitations. Small group projects to create prototypes. Algorithms, complexity, and worst-case analysis. Backdoor and Frontdoor adjustment, introduction to the do-calculus. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets. Prerequisites: Probability and statistics, instruments of the financial markets, and asset pricing models, Prerequisites: see notes re: points 0.00 points. Prerequisites: Linear programming, linear algebra, and computer programming. Prerequisites: (ECONUN1105) Prerequisites: Faculty adviser's permission. Topics include project selection, project teams and organizational issues, project monitoring and control, project risk management, project resource management, and managing multiple projects. Systems integration for successful operation of a spacecraft. Covers working knowledge of quantitative methods and data mining techniques applied to marketing and customer relationship management. IEORE6617Machine Learning and High-Dimensional Data Analysis in Operations Research. 3.00 points. Introductory course for overview of modern approaches and ideas of operations research and data analytics. NOTE: Course information changes frequently, including Methods of Instruction. This is also required for students in the Undergraduate Advanced Track. Covers the use of writing probabilistic models for data-generating processes, using Bayesian Methods/MCMC to solve such problems. Unconstrained and constrained nonlinear optimization involving continuous functions. Prerequisites: (IEORE4700) Easiness 0 Consideration to environmental factors, training and documentation. Write better code with AI. 3.00 points. Teaches foundations required to use probability in applications, but course itself is theoretical in nature. hashing, trees, queues, lists,priority queues. Surveys tools available in Python for getting (web scraping and APIs) and visualizing data (charts and maps). IEORE4511Industry Projects in Analytics Operations Research. 3.00 points. IEORE4575TOPICS IN OPERATIONS RESEARCH. For graduate students: instructor's permission is required. Case study and pricing of structures and products. Prerequisites: (IEORE3106) or (IEORE4106). Corequisites: IEORE4404. IEORE4523-Data-Analytics Public. Marketing Analytics: select at least (9 credits) from the following: 3. Object-oriented programming and database development for building financial data and risk systems; Python and Python's scientific libraries; basic database theory, querying and constructing databases; basic risk management and design of risk systems. Case studies supported by lectures focused on collecting and analyzing skills, client/market data, client interview techniques, and application of quantitative and qualitative methodologies. Prerequisites: (IEORE3608) or (IEORE4004) and basic knowledge of nonlinear and integer programming. IEORE4712BEHAVIORAL FINANCE. Overview of the con- temporary financial system, focusing on innovations of the past few decades that have changed how financial risk is generated and distributed among market participants, such as the growth of non-bank financial intermediaries, the increased prevalence of leverage and liquidity risk, and the development of structured credit products. Connections between the needs of a global enterprise, the technology and methodology needed for manufacturing and product development, and strategic planning as currently practiced in industry. Measurement techniques (A/B testing, validation, correlation, etc.) Enables students to master an array of fundamental operations management tools adapted to the management of health care systems. Required for undergraduate students majoring in OR:FE and OR. Not offered during 2023-2024 academic year. Program in Financial Engineering students, offered during the summer session. Program in Financial Engineering students, offered during the summer session. It exposes students to the striking differences between the model-based (static, thermodynamic/SDE model solutions) behavior predicted for stocks and options and their real (often quite different) behavior. Elementary introduction to Brownian motion and geometric Brownian motion. IEORE4701STOCHASTIC MODELS FOR FIN ENG. Prerequisites: (IEORE3658) and (IEORE4307) or (IEORE4150) or (STATGU4001) and familiarity with R or SAS. IEORE4405PRODUCTION SCHEDULING. 4.50 points. Introduction to the design and analysis of efficient algorithms. Jump diffusion models. 3.00 points. IEORE4560THE LEAN LAUNCH PAD. IEORE4199MSIEOR Quantitative Bootcamp. 3.00 points. Prerequisites: see notes re: points Prerequisites: Approval by a faculty member who agrees to supervise the work. IEORE4738PROGRAMMING FOR FE 1. 3.00 points. Prerequisites: (IEORE3608) and (IEORE3658) and computer programming. IEOR E4312 Applications of OR & AI Techniques in Marketing (1.5) IEOR E4650 Business Analytics. Contains a group project component that will require students to gather, store, and analyze a data set of their choosing. 3.00 points. Mathematical techniques and testing strengths and limits in practice on relevant applications. IEORE4406FAC LOC,ROUTING,NETWORK DESIGN. Large scale applications from signal processing, collaborative filtering, recommendations systems, etc. 3.00 points. IEORE4715COMMODITY DERIVATIVES. 3.00 points. The two strands of the course are brought together to help understand how the financial crisis arose and is playing out, examining the mechanics of runs and the behavior of asset prices during crises. 3.00 points. Packages. This course is aimed at MS and undergraduate students who have already had a basic course in stochastic modeling such as IEOR 3106/4106. Prerequisites: A course on optimization models and methods (at the level of IEOR 4004) and a course on linear algebra. Theory and geometry of linear programming. Required for undergraduate students majoring in OR:FE. The emphasis is on familiarizing the student with the nature of the foreign exchange market and those factors that make it special among financial markets, enabling the student to gain a deeper understanding of the related market for derivatives on foreign exchange. IEEE Xplore I/O Docs IEORE4526ANALYTICS ON THE CLOUD. 3.00 points. IEORE6712STOCHASTIC MODELING II. MSE Concentrations | MSE - Columbia University Moreover, we will discuss modern issues such as bicycle sharing, on-demand car and delivery services, humanitarian logistics, and autonomous vehicles. IEOR E4650 - Business Analytics Description Prepares students to gather, describe, and analyze data, using advanced statistical tools to support operations, risk management, and response to disruptions. Sophisticated modeling of requirements optimization and dependencies, risk management, probabilistic scenario scheduling, verification matrices, and systems-of-systems constructs are synthesized to define the meta-workflow at the top of every major engineering project. This is a follow-up to IEORE3608 and will cover advanced topics in optimization, including integer optimization, convex optimization, and optimization under uncertainty, with a strong focus on modeling, formulations, and applications. Required of all incoming MSFE students. Independent work involving experiments, computer programming, analytical investigation, or engineering design. Prerequisites: PhD-level Linear Programming. Note: restricted to IEOR MS students. Core Curriculum | MSE | ACADEMIC ADVISING, FALL 2018 MS in INDUSTRIAL Prerequisites: Obtained internship and approval from faculty advisor. 3.00 points. Introduction to human spaceflight from a systems engineering perspective. IEORE4524ANALYTICS IN PRACTICE. Prerequisites: Linear algebra. *SIEO W4150 is the same as IEOR E4150. Emphasis on problem-solving and working with data. 3.00 points. Prerequisites: IEORE4707 Refer to course syllabus. The strategies and technologies of global manufacturing and service enterprises. Introduction to the economic evaluation of industrial projects. Corequisites: IEORE4706,IEORE4702This graduate course is only for M.S. Host and manage packages. Networks are ubiquitous in our modern society. A required course for undergraduate students majoring in OR:EMS. Includes multidisciplinary perspectives involving Statistics, Psychology, and Marketing. IEORE6704QUEUING THEORY APPLICATIONS. IEORE4533Performance, Objectives, Results Using Data Analytics. 0.00 points. Survey of different approaches to causal inference with an emphasis on applications. 3.00 points. Course Description IEOR students only; priority to MSBA students. 0.00 points. 3.00 points. Option theory; Black-Scholes equation and call option formula. 0.00 points. Prerequisites: IEOR E3402, IEOR E4000 or instructors permission. User or operator limits and potential in sensing, perceiving decision making, movement coordination, memory, and motivation. 3.00 points. Production scheduling. CSORE4010GRAPH THEORY: COMBINATL VIEW. Focuses on The Think Bigger Innovation Method, uses decision-making theory, cognitive science, and industry practice to facilitate creativity and innovation. 3.00 points. IEORE4723TOPICS IN QUANTATIVE FINANCE. 0.00 points. Additionally, fundamental concepts such as optimality conditions and convergence, principle focus on practical optimization methods. 1.50 point. 1.50 point. In the course of developing these applications, we review topics of interest to OR:FE in a holistic fashion. Class Last Taught Instructors; IEOR E1000 Frontiers in Operations Research and Dat Frontiers in Operations Research and Dat Applications to industrial products, tools, layouts, workplaces, and computer displays. Prerequisites: basic knowledge in programming (e.g. Introduction to human spaceflight from a systems engineering perspective. 3.00 points. IEOR E4523 Data Analytics (IEOR E4501 is a co-requisite) IEOR E4525 Machine Learning FE & OR IEOR E4526 Analytics on the Cloud (IEOR E4523 is a prerequisite) IEOR E4540 Data Mining for Engineers IEOR E4572 Visualization & Storytelling with Data (2nd Half; 1.5 credits) Operations & Analytics Concentration (Select at least three (3) courses) DROM B8106 Operations Strategy (For Spring 2020, this course has been extended to 3 credits) IEOR E4525 Machine Learning for Financial Engineering & Operations Research. IEORE4312Application of OR AI Techniques in Marketing. Final reports required. Prerequisites: Computer programming or instructor's approval. IEORE6711STOCHASTIC MODELING I. The goal is to get the latest sector performance data from the US markets, and to get the total 3.00 points. 3.00 points. Prerequisites: (IEORE3608) or (IEORE4004) and (IEORE3106) or (IEORE4106) 3.00 points. Overview of space environment needed to sustain human life and health, including physiological and psychological concerns in space habitat. An advanced course on reinforcement learning offered at Columbia University IEOR in Spring 2018 . IEORE2261ACCOUNTING AND FINANCE. Prerequisites: optimization, applied probability, statistics or simulation. Each offering of this course is devoted to a particular sector of Operations Research and its contemporary research, practice, and approaches. Response Format (Options are json or xml. IEORE4611DECISION MODELS AND APPLIC. IEOR E4523 Data Analytics Fall x Spring x IEOR E4525 Machine Learning for Financial Engineering & Operations Research Fall x Spring x IEOR E4526 Analytics on the Cloud* . Spring 2023 Industrial Engineering and Operations Research E4523 section V01 DATA ANALYTICS: Call Number: 18083: Points: 3: Grading Mode: Standard: Approvals Required: None: Instructor: Uday Menon: Type: LECTURE: Method of Instruction: On-Line Only: Course Description: IEOR students only; priority to MSBA students. Prerequisites: (STATGU4001) Prerequisites: (IEORE4701) IEORE4721TOPICS IN QUANT FINANCE. 3.00 points. If topics are different then this course can be taken more than once for credit. Hardeep Johar at Columbia University | Coursicle Columbia Special focus will be placed on high-performance numerical applications that interact with a graphical interface. Must obtain waiver for E4101. Teams are fully supported in devising prototypes and actualizing proposed solutions. Brief overview of natural language processing, network analysis, and big data tools available in Python. Applications to various industries including service, airlines, hotel, resource rentals, etc. PDF Ieor Department Spring 2019 Course Offerings IEORE6706QUEUEING NETWORKS. 3.00 points. IEOR E6617 Machine Learning & High-Dimensional Data Analysis in OR Fall x Spring IEOR E8100-001 Matching Markets & Algorithms (Please seek approval from your faculty advisor . Prerequisites: (IEORE3658) and (IEORE4307) or (STATGU4001) and computer programming. Conceptual and mathematical principles underlying these techniques, and practical issues that arise in their implementations in the Microsoft Excel/VBA and other programming environments. IEORE3899Research Training. IEORE4709STATISTICAL ANALYSIS AND TIME SERIES. 1.50 point. Prerequisites: (COMSW3134 or COMS W3136COMS W3137) and (COMSW3203) Introduction to the design and analysis of efficient algorithms. The first half of the course is oriented toward the design and implementation of algorithms, while the second half is more theoretical in nature and relies heavily on material covered in prior probability courses. Focus on advanced statistical techniques for a career in data science or business analytics. Prerequisites: (STATGU4001) and (IEORE4106) Prerequisites: Refer to course syllabus. IEOR E4523 DATA ANALYTICS: 14 Documents: Uday Menon: IEOR 4524 4524: 10 Documents---IEOR 4742 4742: 46 Documents---IEOR 4540: 4 Documents---IEOR 4999: 1 Document--- Characteristics of commodities or credit derivatives. Practice both theory and applications using Python programming. Consists of lectures, recitations, weekly homework, and in-class exams. The emphasis is on modeling and the choice of appropriate optimization methods. MS IEOR students only. Prerequisites: COMSW3134, COMSW3136, or COMSW3137, and COMSW3203. Uday Menon at Columbia University | Coursicle Columbia DATA ANALYTICS - Columbia University Required for undergraduate students majoring in OR:EMS. Focus on the management and consequences of technology-based innovation. Prerequisites: IEORE4101 Introduction to math finance, knowledge of working as a "Quant" in investment banking, hedge funds, algo shop, HFT firm, Fed, Exchange, SEC, IMF, back office, mutual fund, as a trader in risk management, product development, model validation, compliance, reporting, academia. The end result is a dramatic increase in focus on these markets from all aspects of the financial markets, including the quantitative end. Introduction to both discrete and continuous-time Markov chains; introduction to Brownian motion. Summer 2020 Courses - Columbia University Engineering We will address problems such as optimizing the routes of cars and delivery trucks, positioning emergency vehicles, and controlling traffic behavior. Prerequisites: (COMSW3134 or COMS W3136COMS W3137) and (COMSW3203) 3.00 points. CSORW4231ANALYSIS OF ALGORITHMS I. IEORE4562Innovate Using Design Thinking. IEORE4707FE CONTINUOUS TIME MODELS. 3.00 points. Obtain data from files (csv, html, json, xml) and databases (Mysql, PostgreSQL, NoSQL), cover the rudiments of data cleaning, and examine data analysis, machine learning, and data visualization packages (NumPy, pandas . IEEE - IEEE DataPort DROM B8110 Business Analytics Strategy. IEORE4106STOCHASTIC MODELS. Conceptual and practical understanding of structured and hybrid products from the standpoint of relevant risk factors, design goals and characteristics, pricing, hedging and risk management. Prerequisites: B.S. Probability and simulation. Advanced Topics: Causal Survival Analysis, Time-Varying Treatments, Competing Events. GitHub IEOR E4523 - Data Analytics at Columbia University - Coursicle IEORE4408RESOURCE ALLOCATION. Required for undergraduate students majoring in IE. Deterministic mathematical programming models for capital budgeting. Multiple projects and constraints. Risk management models and tools; measure risk using statistical and stochastic methods, hedging and diversification. Perishable and/or limited product and pricing implications. Deterministic and stochastic demands and lead times. 1.00-3.00 points. Automate any workflow. 3.00 points. IEORE4799MSFE Quantitative and Computational Bootcamp. IEOR Students Only; Priority to MSOR Students. Survey tools available in Python for getting, cleaning, and analyzing data. ), discussions on topics in credit, foreign exchange, sovereign ad securitized marketsprivate equity and hedge funds, etc. Selected topics of interest in area of quantitative finance. MEIEE4810INTRO TO HUMAN SPACE FLIGHT. Explores how new industries are created, how existing industries can be transformed by new technologies, the linkages between technological development and the creation of wealth and the management challenges of pursuing strategic innovation, Prerequisites: Obtained internship and approval from faculty advisor. Call numbers for CVN courses: http://www.columbia.edu/cu/bulletin/uwb/sel/VDEO_Spring2021.html See our How To Register guide before registering for courses.