DATE
September 1-24 2023
We are seeking projects that work with data related to a topic TBD, with a focus in one of the following dimensions:
How did the theme affect aspects of Dimension A. Can you use data to inform paths towards a solution?
The theme drastically impacted Dimension B, resulting in X and Y. Can you use data science to identify those impacted the most and suggest changes?
How do we tackle the issues brought up by the theme while accounting for Dimension C?
In what ways can Dimension D affect the theme? What areas of Dimension D affected the theme the most?
Vancouver Datajam 2021 is a virtual one-week, hackathon-like event where participants develop their coding skills and met other members of the community. Participating groups includ RLadies, PyLadies, SFU Scientific Programming, Data for Good and Women in Data Science.
For the 2021 Datajam, we use data and programming to understand how our communities were impacted, and through those insights identify roads towards recovery. Datajam participants will work to understand, visualize, interpret and suggest possible steps our community members can take from the COVID19 pandemic. This free social coding event brings together Canada’s young programmers, scientists and citizens with the common goal of learning, networking and improving the state the pandemic has left us in.
The event kicks off with a day of workshops in Python, R, GitHub and Julia hosted on September 18. Pre-formed teams will then have the option to work asynchronously from September 19 - 24, and socialize with others during this time. On September 25, participants will have a dedicated day-long coding session along with mentors and team leads, followed by a career panel. Our aim is to foster a beginner-friendly environment and to increase the visibility of femme-identified individuals, WoC and gender minorities in the fields of data science and technology. If you have any questions or concerns about the event please contact vancouverdatajam@gmail.com
Our events are always open to everyone, especially those coming from marginalized backgrounds and gender minorities.
