UBC MDS

During the last two months of the UBC Master of Data Science program (typically May & June each year) we have Capstone projects, in which our students work in teams of ~4 students with an external capstone partner and a UBC mentor to address a question facing the capstone partner’s... [Read More]

R and Python are the two leading languages used in industry and academia for data analysis. Thus, to best prepare students in the University of British Columbia’s course-based, professional Master of Data Science (MDS) program to be competitive and perform on the job market, we have made an explicit decision... [Read More]

How can we train effective data scientists? Traditional lecture/lab-based courses typically involve prescribed and well-defined examples, and we found this format very effective for foundational courses that focus on a particular area of statistics, machine learning or computer programming. However, real-world data science differs greatly from these courses: data is... [Read More]

One of the things that drew to me data science is its applicability to pretty much any field you can name: technology, healthcare, finance, retail, education, government, entertainment, agriculture, real estate, etc. There’s no domain too large or small and no organization that would not benefit from having a data... [Read More]

On April 6, 2019, EasyMarkit hosted their first Hackathon in Vancouver where teams were asked to offer an AI solution to improve patient communication. My team (Bailey Lei, Alex Pak, Betty Zhou) was awarded first place based on the accuracy of our model in predicting communication response from patients. [Read More]