Renewable Energy with AI and Data Science: Geology and Geophysics

Gain the expert skills needed in geology, near-surface geophysics and computation, to characterise the shallow subsurface for a broad range of renewable energy applications.

You will examine how data science, numerical methods and machine learning can help solve problems in the renewable energy sector.

You will develop an understanding of the geological, geotechnical and geophysical knowledge and data essential to develop ground models for renewables projects.

You’ll gain exposure to geophysical surveying equipment, and get hands-on experience with real-world data. You’ll also have the opportunity to work on real-world problems through an independent project in an area of your choice.

Exposure to industry will be provided through guest lectures, seminars and the option to conduct your independent project in an industry placement.

This course is suitable for those from a geoscience, physical science or engineering background looking to advance their computer science skills applied to renewable energy problems. This also includes those in industry looking to transition to the renewables sector.

This course is part of the Ada Lovelace Academy, an initiative from the Department of Earth Science and Engineering aiming to deliver gender-balanced post-graduate education in computational subjects to solve the science and engineering challenges of the 21st century.