Data + Python @ NYU Stern

Data Bootcamp

A course at NYU Stern exploring economic and financial data with the Python programming language. The course was developed by Stern faculty and students with the assistance and support of executives at Amazon. The immediate goal is to train students to succeed as summer interns and full-time employees of technology companies, but the same skills are valued in finance, marketing, consulting, media, and other areas. We think of it as literacy for the modern age.

More concretely, the course is designed to (i) introduce students to sources of economic, financial, and business data and (ii) give programming newbies a sense of how modern software – in this case Python – makes life easier and more interesting. We’ll let data speak for itself. As for coding: It’s a skill that opens doors to new career opportunities. You can do lots of things in Excel, but if you value your time – and you should – you’ll find you can do more, and do it more quickly, with a modern programming language. We like to say we do it because we’re lazy, laziness being a synonym here for efficiency.

If that doesn’t convince you, there’s more on our FAQ.

Quick links: Syllabus | Book | Project Guide | Discussion Groups (UG | MBA)

Class Outlines can be found under Topic outlines & links (look left).
Code Practice can be found in the same place – and under Due dates (ditto).

Spring 2017 schedule

Undergrad: ECON-UB.0232, Tuesday and Thursday, 11:00am-12:15pm, Tisch LC-25, January 24 to May 4

MBA: ECON-GB.2313, Tuesday, 1:30pm-4:20pm, KMC 3-90, January 31 to May 2

Future: We expect to offer sections in Fall 2017.

Contact information

Daniel Csaba: csaba.daniel@gmail.com

Balint Szoke: balint.szoke@gmail.com

UG section
Jihyun Kim, teaching fellow, jihyun@nyu.edu, Office hours: Wednesday 4:00pm-6:00pm, KMC 7-100 (pc: 2015)

MBA section
Jihyun Kim, teaching fellow, jihyun@nyu.edu, Office hours: Wednesday, 4:00pm-6:00pm, KMC 7-100 (pc: 2015)

Other materials

In addition to the quick links at the top, keep in mind:

Before the first class