2021/22 Vector Scholarship in Artificial Intelligence recipients announced
“Gaining broad technical skills in artificial intelligence and data science isn’t actually that challenging,” recognized Jaskirat Bhatia. “You can find countless tutorials on Youtube that will teach you the basics. But they can’t tell you which tools to apply to which problems. They can’t guide your learning in any way.” That’s where the Master of Data Science and Artificial Intelligence (MDSAI) comes in.
A self-described “lifelong technology enthusiast,” Max Niebergall enrolled in the Master of Data Science & Artificial Intelligence (MDSAI) program to launch an impactful career in data science.
Part-time admission to MDSAI graduate program now available!
The Public Health Agency of Canada is recruiting volunteers to help with contact tracing and case recording. Future MDSAI student starting Fall 2020, Max Niebergall, is one of more than 34,000 people who have registered.
Data Science hosts first industry networking event
Melissa McCorriston has received a Vector Scholarship in Artificial Intelligence from the Vector Institute. These $17,500 scholarships recognize promising scholars and researchers in Ontario and support their further studies in a top provincial artificial intelligence–related master’s program.
Haonan Duan has received a prestigious Vector Scholarship in Artificial Intelligence from the Vector Institute.
PhD student Alireza Heidari and Professor Ihab Ilyas at the Cheriton School of Computer Science along with international colleagues have developed a novel tool to manage the quality of your data. Called HoloClean, this revolutionary tool is the first to use artificial intelligence to sift out dirty data and correct errors before processing it.
Organizations looking to benefit from the artificial intelligence (AI) revolution should be cautious about putting all their eggs in one basket, a study from the University of Waterloo has found.
In a study published in Nature Machine Intelligence, Waterloo researchers found that contrary to conventional wisdom, there can be no exact method for deciding whether a given problem may be successfully solved by machine learning tools.