Course Code: gi2bs
Duration: 2 hours
Overview:

Objective: Teach the team how to apply AI for predictive analytics in geospatial intelligence, using machine learning models to make predictions based on geospatial data.

Course Outline:

 

Agenda:

 

Introduction to Predictive Analytics (15 minutes)

  • Overview of predictive analytics and its importance in geospatial intelligence.
  • Examples of predictive models in geospatial applications.

AI Tools for Predictive Analytics (15 minutes)

 
  • Introduction to predictive analytics tools (e.g., scikit-learn, XGBoost, TensorFlow).
  • Demonstration of a selected tool.

Hands-On Exercise: Building Predictive Models (30 minutes)

  • Practical exercise: Use an AI tool to build a predictive model using geospatial data (e.g., predicting land use changes, weather patterns).
  • Training a regression or classification model using scikit-learn.

Evaluating Model Performance (30 minutes)

  • Techniques for evaluating and improving model performance.
  • Practical exercise: Evaluate the predictive model using metrics like accuracy, precision, and recall.

Q&A and Discussion (30 minutes)

  • Addressing questions and discussing best practices for predictive analytics in geospatial intelligence.
  • Exploring potential use cases and applications in the team's projects.

Materials Needed:

  • Laptops with internet access.
  • Access to predictive analytics tools (e.g., scikit-learn, TensorFlow).
  • Sample geospatial datasets for exercises.