The era of spatial data science has arrived. Fueled by the need to analyze massive collections of data and renewed interest in artificial intelligence, the demand for data scientists is rapidly growing. However, educating future data scientists is challenging, in fact, a moving target. Researchers frequently introduce new algorithms and analysis methods. As a result, knowing which aspects of spatial data science to teach is often the most challenging part of course design.
One approach to safeguarding our course content from these rapid changes is to focus on teaching the broader competencies in data science in addition to leveraging the technology built around them. In this webinar, we'll explore the core competencies of data science and demonstrate analytical workflows that can help build them.
