Short Course: Data Science for Physicists I

ORAL · MAR-SH01 · ID: MAR-SH01

Data science is playing an ever increasing role in physics. In this two day tutorial, we will introduce data science as it applies to a variety of fields in physics. The first day of the course is an introduction to the fields of data science and machine learning (ML) as they apply to physics data. We will then provide an introduction to machine learning, including both regression and classification algorithms. This session will explain why neural networks work and describe the practical steps needed to train a model, such as feature engineering, hyperparameter tuning, and validation. We will conclude the first day of the tutorial with an introduction to unsupervised learning techniques (including clustering and random forests), as well as a session which will introduce both neural networks (NNs) and convolutional networks (CNNs). The second day of this course will provide sessions on advanced topics in data science and machine learning. The first three sessions will cover graph neural networks (GNNs) and large language models (LLMs), focusing on their applications to physics. The final four sessions of the tutorial will cover a range of applications of both machine learning and data science.

Note: This is part one of a two-part course

Price:

• Students: $250
• Non-students: $300