Managerial Statistics
- F 3:45 p.m.-6:45 p.m.
- T 8:30 a.m.-4 p.m.
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Instructor:
Cyrus Mohebbi
Info -
Instructor:
Faculty
h-index: 37 Info - 3 points
OPERATIONS MANAGEMENT
- MWF 9 a.m.-10:30 a.m.
- MWF 10:50 a.m.-12:20 p.m.
- MWF 2:20 p.m.-3:50 p.m.
- MWF 4:10 p.m.-5:40 p.m.
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Instructor:
Nicola Rosaia
Info - 1.5 points
Business Analytics II: Foundations of AI
Business Analytics 2
- MU 9 a.m.-5 p.m.
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Instructor:
Charles R Guetta
Info - 1.5 points
Business Analytics III: Modern AI, Deep
- T 2 p.m.-6 p.m.
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Instructor:
Charles R Guetta
Info - 1.5 points
Python for MBAs
From the ads that track us to the maps that guide us, the twenty-first century runs on code. The business world is no different. Programming has become one of the fastest-growing topics at business schools around the world. This course is an introduction to business uses of Python for MBA students.
In this course, we’ll be learning how to write Python code that automates tedious tasks, parses and analyzes large data sets, interact with APIs, and scrapes websites. This might be one of the most useful classes you ever take.
Required Course Material
Students must have a laptop that they can bring to class – Mac or PC is fine, as long as your operating system is up to date (at least Windows 10 and Mac OS 11).
This course does not require a textbook. (Optional Reading: Python for MBAs, Griffel and Guetta)
Any required readings will be provided via Canvas.
Slides and files will be uploaded to Canvas after each class.
Students will need to complete an introductory Python class (https://courseworks2.columbia.edu/courses/152704) and pass the Basic Python Qualification exam (https://www8.gsb.columbia.edu/courses/python#basic_qual) before the first day of classes.
- S 8:30 a.m.-11:30 a.m.
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Instructor:
Sunny Israni
Info - 1.5 points
Business Analytics II: Foundations of AI
Business Analytics II: AI
This course extends and deepens the material you learned in business analytics. We will apply these methods in more unstructured and diverse situations, introduce new analytics tools and methods (including Tableau Visualization, text mining, and random forests), and study a modern framework for overfitting reduction called regularization that underlies much of modern machine learning. This course does not require coding or knowledge beyond Business Analytics, but the mathematical sophistication level will be somewhat more advanced.
- MU 9 a.m.-5 p.m.
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Instructor:
Charles R Guetta
Info - 1.5 points
Business Analytics III: Modern AI, Deep
Business Analytics III: A
- T 2 p.m.-6 p.m.
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Instructor:
Charles R Guetta
Info - 1.5 points
The U.S. Healthcare Industry
- MTWRF 9 a.m.-1 p.m.
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Instructor:
Carri Chan
h-index: 17 Info - 1.5 points