The process of creating maps has gone through radical changes over the past few decades. What was once a specialized craft using expensive tools and carefully curated data has now become something anyone can do as new, easy-to-use, and inexpensive (often free) tools have allowed professionals and hobbyists alike to create beautiful and informative maps with open data. This half-day course will briefly review the principles of mapping, discuss sources of online spatial data, and survey some of the open-source tools available, including QGIS and CARTO. Participants will get the opportunity to use these tools in a hands-on exercise.
A full-day course in basic spatial concepts and key features of QGIS for loading, styling, and analyzing spatial data with an emphasis on using real-world data to answer interesting and important analytical and operational questions. No experience with spatial data or GIS applications is assumed.
A full-day course for up to 20 employees familiar with how to load and visualize spatial data in QGIS or another GIS applications. The course covers how to load, process, and analyze real-world data using an open-source spatial relational databases with QGIS to answer interesting and important analytical questions.
A full-day course for up to 20 employees familiar with how to load and visualize spatial data in QGIS or another GIS applications. The course covers advanced techniques of data extraction, transformation, and loading, as well as key concepts in data management, documentation, and analytical integrity using real-world data using an open-source spatial relational databases with QGIS to answer interesting and important analytical questions.
A one-day class reinforcing the skills necessary to leverage a geographic information system (GIS) to clean, process, and visualize government open data. The class introduces key concepts and skills necessary to use a GIS for data analysis, reinforcing the problem ideation and process mapping skills taught in Introduction to Data Analysis. Working collaboratively in small groups, participants will develop an analytical question they explore throughout the class, presenting their data story at the end of class for constructive feedback.