BIG DATA METHODS FOR ECONOMICS
BIG DATA METHODS FOR ECONOMICS
2025 Fall Term
Economics 350
This is an applied course that covers a wide range of big data analytics techniques relevant to economic and business applications. This course offers a hands-on experience with advanced tools to tackle real-world business and socio-economic challenges. Topics include: building machine learning models to solve issues ranging from income and social inequality to predicting whether a loan application will be risky; natural language processing to classify texts, analyze email communications, and investigate corporate fraud; time-series modeling to forecast stock prices and predict trends; and spatial data analysis for examining violent crimes and home foreclosures.
Other Requirements: PREREQ: ECON 245 AND ((COBE MAJOR: 2.50 CUMULATIVE GPA) OR (NON-COBE MAJOR/MINOR/COBE MINOR: 2.00 CUMULATIVE GPA))
Class Schedule
Disclaimer
- This schedule is informational and does not guarantee availability for registration.
- Sections may be full or not open for registration. Please use WINS if you wish to register for a course.
| Section Details | Meeting Details & Topic | Instructor | Syllabus | ||
|---|---|---|---|---|---|
|
22-LEC 3426
3 Units
|
09/02 - 12/06 (1) |
Narendra Regmi
|
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| ONLINE | |||||
|
22W-LEC 3427
3 Units
|
09/02 - 12/06 (1) |
Narendra Regmi
|
|||
| ONLINE | |||||
| PREREQ: MUST BE ADMITTED TO AN ON-LINE MAJOR | |||||
