When: July 9, 2015, 7 p.m.

Where: WeWork

220 N Green St, Chicago, IL 60607


  • Formula One Data Visualization and Interpretation: adventures in mentorship
    (0:07:00 Minutes)
    By: Seth Difley
    We participated in the Chipy mentorship program. Our plan for the mentorship was to use Python to visualize and interpret Formula One racing data. Join us to hear about the triumphs and obstacles we encountered along the way.
  • Building a Temperature Control Program for Monitoring Aquaculture Tanks Using Raspberry Pi and Python
    (0:07:00 Minutes)
    By: Thao Nguyen
    Growth of the Mentee as a Pythonista I have turned from totally no experience with Python to gaining a good amount of knowledge in this language. I have learned from the very basic syntaxes to writing functions, then writing functions for different types of data (list, string, integer, decimal, float, epoch, threshold…) to serve various purposes; I know how to install redis, bokeh and flask for data acquisition, storage and performance; I also learned how to send an email alert from the Raspberry Pi with Python, thanks to the hackathon midterm meetup and my mentor. And because our project covers a wide range of activities, I have learned a lot of the fundamental elements of Python as well as programming in general. Above all, the best thing I have learned about Python through this Mentorship program is being confident and feeling more comfortable with it. Before this project, I wasn’t really sure about Python. Is it what I want or I might be better off with other languages? But after finished the project, I can say it was fun, and it serves well what I want to do. So I decided to move forward with it. And even though this is my very first programming language, but the dynamic from its strong supportive community, rich wonderful open sources and inspiring opportunities like this Mentorship program, all makes me feel that Python is a good choice. The Mentor's role When I asked my mentor for his advices on learning programming, he told me that to him, the best way to learn is doing projects, just like what we are doing. And that is so true. Sometimes I feel like the best way of learning how to swim is just jumping into the water, like doing a project; it can be scary, uncertain, and possibly failed, but it can also be very exciting and thrilling. Of course, one should only jump with a life preserver if she never knows how to swim before. And our mentors are life preservers. For a novice, it could be very confused at first of where to go, what direction to take, or how to get there; and easy be overwhelmed by too much information. The life saver may not be able to tell you what direction to take either, but at least, it will help you have some time to think and to practice before you decide your next moves. Obviously, a mentor is much better than a life saver, because no life saver can talk nor answer questions; and the best part is, they have a lot of experiences in their hands and are willing to share them with you. Thao Nguyen
  • Quantopian Trading
    (0:07:00 Minutes)
    By: Sean Ware
    Brief introduction to the Quantopian api which is used for trading financial assest with python.
  • Why learning process matters to student dev's
    By: Lane Campbell
    I took up learning Python and Web Development early this year. I started attending Django lessons held by folks in the community. After the lessons students had trouble finding help learning together. To help everyone organize I founded the Django Study Group. I've been learning for the last six months but I am still a student. I joined the Chipy mentorship program to learn from a local professional Python developer. While enrolled in that I took the opportunity to join a student team led by Brian Ray for more experience learning to code. It was working alongside Brian that I learned the importance of how you build software.
  • Machine Learning with Python
    (0:07:00 Minutes)
    By: Alexander Flyax
    I will briefly describe my journey into applied machine learning using Python packages like scikit-learn and statsmodels.