GEBA Internship Program is a practical 8–12 week learning experience offered during the June–September period for high school and university students interested in GeoAI, data science, remote sensing, coding, environmental intelligence, and real-world project development.
The GEBA internship introduces students to data science, coding, visualization, digital tools, and practical problem solving through hands-on learning and team-based projects. The program is designed to make technology and data more approachable by connecting everyday questions and real-world challenges with practical exercises and project development.
Internship journey with weekly photos, short descriptions, student learning activities, and project milestones.
The internship began with a virtual orientation introducing the program structure, learning goals, and 8–12 week roadmap. Students were introduced to data science, GeoAI, Earth observation, and the team project they will develop throughout the program.
Students learned the fundamentals of data science and how raw data can be organized, explored, and interpreted to answer real-world questions. Hands-on activities introduced basic data analysis workflows and encouraged students to identify patterns, variables, and relationships in data.
Students practiced transforming data into visual information using charts and graphical displays. The activities focused on understanding how visualization can reveal trends, comparisons, and patterns that may be difficult to recognize from raw numbers alone.
Students were introduced to predictive modeling and how data can be used to estimate unknown or future outcomes. They practiced connecting input variables with model results while learning the importance of interpretation, accuracy, and model evaluation.
Students explored Earth observation and learned how satellites and remote sensing provide information about the Earth's surface and environment. They examined spatial imagery and discussed how environmental conditions can be observed and analyzed from space.
Students gained hands-on experience with Google Earth Engine for exploring satellite imagery and geospatial data. They practiced navigating locations, examining Earth observation datasets, and connecting cloud-based mapping tools with GeoAI and environmental applications.
Coming soon
Coming soon
Coming soon
As students build team projects, this section will link to simple web apps, maps, notebooks, dashboards, or GeoAI demonstrations developed during the internship.
GeoAI Lyme Alert — A team project using geospatial data, Earth observation, and AI to develop an interactive Lyme disease risk and alert application.
For internship questions, collaboration, or student participation inquiries, contact GEBA Consulting LLC.