Webinar Recording - Using AI for predicting students at risk
Last week, Ometis hosted a webinar showing the AI and ML facilities within Qlik AutoML. We covered a specific use case for Higher and Further Education but were joined by many, not from those sectors as the principles of what we were showing were universal.
We showed the drag and drop facilities of Qlik AutoML which provide a no-code experience, meaning that even those without deep data science experience can still create models and use AI and Machine Learning to find insights. This particular model explores historical data and makes predictions based on it for the current cohort of students. The questions we answered in the webinar included:
Can we use AI to analyse various data sets and predict students likely to leave their course? This is key in the Further and Higher Education sectors where a significant portion of funding is based upon students completing.
Can we apply what-if analyses that can show the predicted effect of changes to policies on those "at risk students"? Some of the examples we showed included, a change of living circumstances bringing students into college or university accommodation; a change of tutor; assistance with funding and many more.
We have had excellent feedback about this session from universities and colleges, but also organisations from other sectors who can see how it could apply to them too. So, if you are an organisation looking to make AI predictions on your historic data, please do get in touch as we'd love to help.
As mentioned earlier though, the science of predictive analytics can apply to all industries and sectors. Predicting employee or customer churn, inventory stock outs or even, future sales are frequently seen use cases that can also take advantage of this functionality.
Get in touch using the button above if you would like to better understand how Qlik AutoML using Artificial Intelligence (AI) and Machine Learning (ML) can help your organisation.