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NOTE: Course information changes frequently. Please re-visit these pages periodically for the most recent and up-to-date information. | |
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, 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 |
| 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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