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A course exploring economic and financial data with Python at NYU's Stern School of Business. For current information and links to course material, try the Data Bootcamp website.

April 2016. We are offering two sections of Data Bootcamp at NYU Stern in Fall 2016, one for undergrads (ECON-UB.0232, Tuesday and Thursday, 2-3:15) and one for MBA students (ECON-GB.2313, Wednesday nights, 6-9pm). We plan the same for Spring 2017. They are standard for-credit courses at NYU and will be listed on NYU's online registration system.

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 and a selling point in finding a job.

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 the data speak for itself. But coding is an essential skill in the modern world. You can do lots of things in Excel, but if you value your time -- and you should -- you'll find you can use it more efficiently with a modern programming language. We like to say we do it because we're lazy, laziness being a synonym here for efficiency. Former students tell us it's become a key to success in the business world. An alum with strong programming skills worries that this course will make him obsolete.

Data Bootcamp will NOT cover SQL databases. SQL Bootcamp is a separate non-credit course. Same team, same attitude, different content. For more information, scroll down.

You can find more information about the course on the course website. If you have questions, email Dave Backus ([email protected]) or track him down in his office (KMC 7-68) or at the Malt House.

Related courses. Several students have asked how Data Bootcamp compares to other courses with significant programming content. I've put together a list, but I recommend you ask around. Data Bootcamp does two things that are unusual: it's newbie-friendly, and there's a strong emphasis on data. The latter strikes me as important, in the sense that when you learn to program, it's helpful to have a purpose in mind. Ours is to collect and manage data.

Suggestions welcome. Post them at the "Issues" link at the top (look for the exclamation point in a circle) or email Dave Backus at NYU: [email protected]. Thanks in advance.

Licensing. We encourage others to use this material and to acknowledge such use. Here's the boilerplate. On the off chance this crossed your mind, here's Richard Stallman's take on the license, which allows commercial development.

Part of the #nyuecon collection at NYU's Stern School of Business.

Back by popular demand: the second annual SQL Bootcamp @ NYU Stern. This four-session Amazon-approved course is designed to get Amazon's summer interns up to speed so they can hit the ground running. Others may find the same skill set useful. Organized by Professors David Backus and Glenn Okun, the course is designed and delivered by MBA2 Sarah Beckett-Hile.

2016 mini-course. The 2016 edition of SQL Bootcamp consists of four Friday sessions starting March 25 through April 15 and will run from 1:30 to 4:30pm.

Room: KMC 3-65

If you plan to join us:

• Sign up for our Google group to get further information and announcements.
• Download the class file: SQL_Bootcamp_Stern_2016
• Download the syllabus
• Download the Cheat Sheet, which summarizes concepts
• Download and install Anaconda for Python 3.5 by selecting the 64-Bit Graphical Installer

Video links. Class 1 | Class 2 | Class 3 | Class 4

Questions and comments. If you have questions or comments about the class, you can post them on the group. Or contact one of the organizers.

Exit poll. If you use this material, please fill out the (short) exit poll.

Another product of the #nyuecon Python factory @ NYU Stern.