Changes

== The Waterloo Experience (WE) Story ==  

== The Waterloo Experience (WE) Story ==  

An opportunity was presented to Health Canada to be part of the Waterloo Experience - a program which provides students in-demand Artificial Intelligence (AI) and business skill development (co-created with AltaML, Microsoft and Industry/Public partners), team-based project experience, and real-world industry exposure. Health Canada is one of the partners that will bring a business problems to these students so they can apply AI and ML to solve them.  

An opportunity was presented to Health Canada to be part of the Waterloo Experience - a program which provides students in-demand Artificial Intelligence (AI) and business skill development (co-created with AltaML, Microsoft and Industry/Public partners), team-based project experience, and real-world industry exposure. Health Canada is one of the [https://www.altaml.com/news/altaml-announces-collaboration-with-microsoft-canada-university-of-waterloo-and-industry-to-deliver-applied-artificial-intelligence-work-integrated-learning-through-the-we-accelerate-program/ partners] that will bring a business problems to these students so they can apply AI and ML to solve them.  

Decisions informed with data that is driven by risk is a prime focus for all programs in ROEB. Health Canada is proposing to use Site Risk Profiling as the use case for this opportunity. Existing approaches to Site Risk Profiling is being conducted with HC data applied with multi-variant statistical analysis. It is unknown, however, if this approach has biases or gaps that can create risk to the compliance and enforcement mandate. To validate Health Canada’s approach to Site Risk Profiling, we are proposing to leverage public data via Twitter to assess Machine Learning potential and compare our approach to a solution provided by WE Accelerate.

Decisions informed with data that is driven by risk is a prime focus for all programs in ROEB. Health Canada is proposing to use Site Risk Profiling as the use case for this opportunity. Existing approaches to Site Risk Profiling is being conducted with HC data applied with multi-variant statistical analysis. It is unknown, however, if this approach has biases or gaps that can create risk to the compliance and enforcement mandate. To validate Health Canada’s approach to Site Risk Profiling, we are proposing to leverage public data via Twitter to assess Machine Learning potential and compare our approach to a solution provided by WE Accelerate.

== Repository ==

== Repository ==

Click [https://022gc.sharepoint.com/:f:/s/ROEB-POD-TransformationOffice/Eu6lHpqoNrNPtE94pW7HIK4BxqktGLbTq-7E6CZeH4ZFSw?e=486tus here] to access the Sparrow files.

Click [https://022gc.sharepoint.com/:f:/s/ROEB-POD-TransformationOffice/Eu6lHpqoNrNPtE94pW7HIK4BxqktGLbTq-7E6CZeH4ZFSw?e=486tus here] to access the Sparrow files.