Join us this summer to learn more about managing through a crisis, data science,
and more.
The COVID-19 pandemic has created new challenges across the globe, especially for higher education. With uncertainty around enrollment, academic delivery method, finances and more, there are more questions than answers surrounding the future of many institutions.
Darren Catalano, CEO of HelioCampus and former Vice President of Analytics at the University of Maryland Global Campus (UMGC), will share how UMGC weathered a dire financial situation six years ago, highlighting the role of IR on this journey and in times of crisis. He'll also suggest new priorities and areas of focus for IR offices that are especially important as institutions look to use data to inform their planning and navigate this unprecedented crisis.
Data science is a hot topic in higher education and beyond. But what is it really? This webinar will cover introductory data science concepts like what a "classification model" is, examples of predictive modeling products you interact with every day, how we approach data science at HelioCampus, and what models trained on past data can and can't predict when the world changes in unexpected ways.
Renee Teate, Director of Data Science at HelioCampus and creator of the "Becoming a Data Scientist" podcast and @becomingdatasci twitter account, will lead the discussion. If you are interested in learning more about data science and predictive modeling, you won't want to miss this webinar.
From the humble bar chart to advanced predictive algorithms, effective data science programs employ a wide range of tools to answer strategic questions using data. In these highly uncertain times, it is more important than ever that we use all of the tools at our disposal to answer these questions effectively. Beyond simply trying to predict the future, we need to use a comprehensive approach to uncover the stories in the data.
In this webinar, Craig Rudick, Director of Product Strategy at HelioCampus and former Director of Institutional Research and Lead Data Scientist at the University of Kentucky, will discuss techniques, both technical and practical, for designing and implementing a data science program that uses the full range of available tools, and creates the broad and deep knowledge base upon which true data-informed decision making is grounded.
