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Fall 2020 Industrial Engineering and Operations Research E4523 section 001
DATA ANALYTICS

Call Number 11553
Day & Time
Location
TR 11:40am-2:10pm
To be announced
Points 3
Grading Mode Standard
Approvals Required None
Instructor Uday Menon
Type LECTURE
Method of Instruction Hybrid
Course Description Corequisites: IEOR E4501 Co-requisite: IEOR E4501 Tools for Analytics. Survey tools available in Python for getting, cleaning, and analyzing data. 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, ScikitĀ­learn, bokeh) available in Python. Brief overview of natural language processing, network analysis, and big data tools available in Python. Contains a group project component that will require students to gather, store, and analyze a data set of their choosing.
Web Site Vergil
Subterm 09/08-10/19 (A)
Department Industrial Engineering and Operations Research
Enrollment 0 students (80 max) as of 11:34AM Tuesday, August 4, 2020
Subject Industrial Engineering and Operations Research
Number E4523
Section 001
Division School of Engineering and Applied Science: Graduate
Open To Engineering:Undergraduate, Engineering:Graduate
Campus Morningside
Section key 20203IEOR4523E001

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SIS update 08/04/20 11:34    web update 08/04/20 12:19