nhmatheson / data_bootcamp

Materials for a course at NYU Stern using Python to study economic and financial data.

###Data Bootcamp

Materials for a course about economic, financial, and business data based on the Python programming language. It is designed to give (i) students some familiarity with economic and financial data and its uses and (ii) programming newbies a sense of how modern software makes life easier and more interesting. The current plan is to offer two sections of the course in Spring 2016, one for undergrads, the other for MBA students.

More information:

• Course description and FAQ
• Book (first few chapters done, the others will be fleshed out between now and January 2016)

Mini-course. We ran a three-session mini-course in Fall of 2014. The materials are a little terse, but they'll give you a sense where we're headed:

Session 1 | Session 2 | Session 3.

The code files are imbedded, and also posted in the Code directory (scroll to the top of the page).

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

Acknowledgements. This was Glenn Okun's idea, so I should probably thank him, although he really should have done this himself. I do appreciate his support. And I know I should thank Chase Coleman and Spencer Lyon, aka Tom Sargent's Python Team; the three of us put this course together. Paul Backus is our go-to advisor on technical issues. Sarah Beckett-Hile is rapidly adding to our collection of applications and is proof that English majors can code as well as anyone. You may also notice a resemblance to Tom Sargent and John Stachurski's Quantitative Economics, a wonderful Python-based course in dynamic macroeconomic theory. We've used a lot of their material, including their approach to documentation. We thank them for that, and for their advice and encouragement.

Licensing. We encourage others to use this material and to acknowledge such use. Here's the boilerplate. In case you wondered, 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.

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###SQL Bootcamp

Professors David Backus and Glenn Okun proudly present the 2015 NYU Stern School of Business SQL Bootcamp. This five-session non-credit program will be taught by Sarah Beckett-Hile. It follows a popular Python mini-course run last fall.

Sessions. Class sessions will be held on Fridays in KMC 5-90, 2pm to 5pm, starting March 27 and running through April 24.

Before the first class. We will be using the Anaconda distribution of Python 3.4. To install it on your computer, follow these instructions. If you're stumped, come 30 minutes early to our first session.

Announcements. If you want to get announcements about the class, please join our discussion group, a Google Group devoted to this purpose. You can ask questions there, too.

Materials. Also before the first class, you should download these documents and save them in a convenient folder/directory:

• Syllabus
• IPython notebook (essentially a combination of slides and code for the course)
• Python support code (you won't touch this, it runs behind the scenes, but you need it for the notebook to run)
• Cheat sheet: this covers the whole course.

Once you've done this:

• Open Anaconda, then launch "ipython-notebook". This will open a window in your default browser where you can navigate your computer's local folders
• Locate and open the folder where you saved SQL_Intro.ipynb and SQL_support_code.py.
• Click to open SQL_Intro.ipynb (you don't need to open SQL_support_code.py, just make sure it's in the same folder).

Webinar. We have set up a "webinar" for people who cannot be here in person, including alums and other friends of the school. Please register here for SQL Bootcamp at NYU Stern School of Business. After registering, you will receive a confirmation email with information about joining the webinar. The webinar gives you access to a live stream and the ability to ask questions.

Videos. The collection:

Session 1 | Session 2 | Session 3 | Session 4 | Session 5

Please download before playing.

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

Questions and comments. If you have questions or comments about the class, you can post them on the group. Or contact Dave Backus ([email protected]).

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