Machine Learning in Physics

Education facts

Code: 5FY227

This course is designed to introduce undergraduate physics students to the fundamental concepts of machine learning, emphasizing both theoretical foundations and practical applications specific to physics. It covers a broad range of essential machine-learning techniques and models, and addresses the statistical challenges associated with optimizing these methods and evaluating the solutions they produce. Through this course, students will gain a deep understanding of how machine learning can be applied to solve real-world physics problems.

Entry requirements

90 credits including quantum mechanics, electrodynamics, thermodynamics, solid state physics, introductory programming methodology and introductory numerical methods. Proficiency in English and Swedish equivalent to the level required for basic eligibility for higher studies. Requirements for Swedish only apply if the course is held in Swedish.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Machine Learning in Physics

  Umeå University

  Umeå

  Start date: 31 August 2026

  End date: 1 November 2026

  Pace of study: 50 %