By Ian Gormely
April 26, 2022

As part of Vector Institute’s inaugural Introduction to Machine Learning (ML) for Black and Indigenous students, four Canadian post-secondary students were awarded Best Capstone Papers & Presentations. Ade Adeoye, a first-year Master’s student in statistics at the University of Toronto; Jummy David, a second-year postdoc in math and statistics at York University; Dagimawi Eneyew, a second-year PhD student in software engineering at Western; and Wintta Ghebreiyesus, a fifth-year PhD in aerospace engineering at Ryerson; were awarded $375 for their course capstone projects. 

Kicking off in February, the course was open to Black and Indigenous post-secondary students from across Canada. The free, six-week-long online class introduced students to common machine learning algorithms as well as a broad overview of model-building and optimization techniques. 104 students applied and 50 from 18 different post-secondary institutions were accepted. In the end, 29 finished the course, including the final paper, presentation, and Q&A that makes up the capstone project. 

“Our goal was to develop the pipeline of ML and AI talent among Black and Indigenous learners,” says Shingai Manjengwa, Vector’s Director of Professional Development. “After a rigorous six weeks, each student left with a strong foundation on which they can advance their skills in the field as well as connect with a close-knit community of supportive fellow practitioners.” 

“This course gave me the skills needed to efficiently do modelling,” said Siphelele Danisa. “I am now able to work more creatively, which shifts my focus to doing work that is more meaningful and that adds value to society.”

Guest speakers were brought in to share their experiences working as data scientists in areas such as health and finance as well as work around fairness and EDI in the field. 

“The passion and effort of the instructors at the Vector institute combined with their genuine interest in helping their students is quite unmatched,” said Mogtaba Awad Alim. “It makes for a unique learning experience.”

Black and Indigenous people face challenges when entering the artificial intelligence (AI) field and STEM and tech more broadly. By offering the course directly to people who identify with these groups, Vector hopes to increase the opportunities to build AI research and career paths for Black and Indigenous students in Canada. In May, Vector will be welcoming both researchers and applied interns from Black and Indigenous communities, including three members of the Introduction to ML course.

“Vector is committed to making space for greater inclusion,” says Garth Gibson, Vector President and CEO. “We are working towards supporting an increasingly diverse AI ecosystem; courses like the Intro to ML for Black and Indigenous students are important steps towards a more equitable and just future.” 

The next Introduction to Machine Learning course for Black and Indigenous students starts in October of 2022. Applications are now open and you can apply here. For more information about ML classes and internships for Black and Indigenous students, click here.