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SF Python is bringing it's Project Night to Galvanize. It's going to be an evening of learning, hacking, sharing your knowledge, and enjoying food and drinks provided by our venue host Galvanize.

*Don’t forget: save time at check-in by registering for this event via Eventbrite (

Who should attend?

• New to Python and want to work with other Pythonistas

• Experienced devs who want to hack on your work, personal or open-source projects

• Experienced devs who want to mentor others

• Anyone that's interested in our tutorial offerings

The plan:

6:00p Begin check-in

6:50p Introductions: tell us about your project and/or the kind of help you seek

7:00p Make yourself comfortable and start hacking, or attend one of the tutorials

9:30p Wrap up / Door close

**There are a few spaces for bicycle inside Galvanize. Once those slots are filled up, please park your bicycle outside the building.

*Don’t forget: save time at check-in by registering for this event via Eventbrite (

Planned tutorials:

#1 Intro to Python for Data Science by Isaac Laughlin

Data scientists need to know how to code, and Python is the most useful and versatile programming language for doing data science. In this workshop you’ll learn foundational skills for adding Python to your data science and analytics toolbox. You’ll leave this session equipped to write your own Python scripts to analyze data, and instructor recommendations about next steps to take on your pathway to data science.

Level:Beginner friendly!

Instructor: Isaac Laughlin ( teaches Data Science theory and practice as part of Galvanize's 12-week Data Science Immersive course. Prior to joining Galvanize he worked on industry-leading models for automotive price prediction at, built crowd-sourced platform for predicting the future, and was an RA at the Federal Reserve Board. He has a Masters Degree in Operations Research from the University of Wisconsin Madison.

#2 Scientific Computing in Python by Cary Goltermann

Ever wondered if Python can be used as a performant programming language? Come get an introduction to scientific computing in Python. Along the way, you'll learn about an unsupervised machine learning algorithm (k-means), computation vectorization, and Numpy.

Level: Intermediate.

Instructor: Cary Goltermann ( has a background in math and physics and started programming while attending University of Colorado Boulder. He was accepted to a Teaching Assistantship at his alma mater, where he got his chops as a teacher, teaching C programming language and Matlab. Cary went on to attend Galvanize’s Data Science Immersive in Denver in 2015 and was immediately hired as a Data Scientist in Residence, to assist in teaching curriculum to other cohorts. Over a year ago, Cary was hired as a Data Scientist, Associate Instructor in San Francisco. He has a passion for both the theoretical aspects of data science algorithms and the practical ones associated with practicing efficient data science in code. Moreover, he loves sharing that passion through teaching.

#3 (Micro)Python and IoT: Let's hack some hardware by Jeff Fischer

Due in large part to the availability of cheap, low-power, internet-connected microcontrollers, the Internet of Things is taking off. Python developers can get in on the excitement with MicroPython, an implementation of Python 3 that runs on very small devices with no operating system. MicroPython provides the standard Python REPL (read-eval-print-loop) interface, so you can interactively develop and debug applications on these small devices. In this session, you will learn some basic electronics, wire up some sensors to a low-power wireless controller board (based on the ESP8266 microcontroller), load the MicroPython firmware, and interactively write simple applications to read from the sensors. We will also discuss how to connect to other systems via the MQTT messaging protocol and exchange ideas on larger projects that can be built at home for low cost with beginner-level knowledge. Here is the instruction manual ( for the project (still a work in progress).

Level: This tutorial is beginner friendly!

Class size limitation

We currently have 10 boards for the class. People can double up and work together, so we'll limit to the first 20 people who show up on the 18th and express an interest in the class.


Participants are expected to already know Python and how to use the Python Read-Eval-Print Loop (REPL). It is recommended that you are familiar with installing Python packages via pip and with Python's virtual environment tools. No special hardware knowledge is required.

You will need a laptop with a USB port that has Python 2 installed (unfortunately, one of the libraries we'll use to burn the firmware is Python2-only). Mac and Linux are recommended, as we've only tested using those machines. In theory, Windows should work as well.

There are a few software dependencies that you will need to download (the MicroPython firmware, some github repositories, etc.). To save some time on the night of the hackathon, we recommend that you read through the software prerequisites section of the instruction manual ( and download/install the dependencies.

Not interested in any of the tutorials? Bring your own project to hack on or bring your burning questions and we will try to hook you up with devs that can help you out.

Examples of projects to hack on:

• Personal side projects - your web application or personal learning project

• Open source projects - work on open issues or recruit developers for your project

• Work projects - work on anything you like and bounce ideas around

Hope to see you there!

*Don’t forget: save time at check-in by registering for this event via Eventbrite (

**SF Python is run by volunteers aiming to foster the Python Community in the bay area. Please consider making a donation ( to SF Python and saying a big thank you to Galvanize for providing food, drinks, and the venue for this Wed's meetup.