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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information. | |
Spring 2021 Industrial Engineering and Operations Research E4523 section 001 DATA ANALYTICS | |
| Call Number | 13467 |
| Day & Time Location |
TR 1:10pm-2:25pm 633 Seeley W. Mudd Building |
| 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, Scikitlearn, 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 |
| Department | Industrial Engineering and Operations Research |
| Enrollment | 90 students (85 max) as of 8:02AM Sunday, February 28, 2021 |
| Status | Full |
| Subject | Industrial Engineering and Operations Research |
| Number | E4523 |
| Section | 001 |
| Division | School of Engineering and Applied Science: Graduate |
| Open To | Engineering:Graduate |
| Campus | Morningside |
| Section key | 20211IEOR4523E001 |
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