The course is partly based on an EAGE publication (Advances in Gravity and Magnetic Processing and Interpretation by J. Derek Fairhead, ISBN 978-94-6282-175-0). In the first part, various aspects of gravity will be discussed, such as the Earth gravity field, determining anomalies in the global field, establishing the depth of density anomalies, be it spherical or anticlinal and the resolution, which is limited because gravity is a “potential field”. Most promising is the development of gravity gradiometer, whereby gradients in the gravity field can be directly measured with great accuracy. These measurements are less sensitive to airplane and ship movement. In the second part, the Earth’s magnetic field, also a “potential field” will be studied. Being due to the internal dipole source, the inherently more difficult interpretation is simplified by applying a transformation to a monopole field (Reduction to the Pole or Equator). As different causative sources can produce the same surface measurements, non-uniqueness is always present. However, promising developments to mitigate these issues will be shown. Finally, we will discuss and apply the “latest and greatest” that is Machine Learning, a part of Artificial Intelligence, which is step-changing the geoscience world. We will use a standard package called Weka and familiarise ourselves with the “ultimate” open-source software TensorFlow. Exercises will be done using Weka and Google Colab.