An in-depth analysis of crime in the City of Toronto, with a heat map of the most dangerous neighborhoods.
A new way for teachers to build student groups who have complementary skills, using machine learning.
Why data science job descriptions can be so inaccurate, and how to tell which postings you should apply to.
Understanding the hiring process from the inside, and what it means for your application.
How to build a project that employers will actually care about.
On the value of the PhD, the Master’s, and when it’s time to drop out.
Stories of personal data science projects that led to job offers.
Everything you need to know to become a machine learning engineer from scratch.
Tips on how to focus your skills development, and find the right kind of data science job.
Getting noticed in a world of unremarkable people.