Data Science for Astrophysicists

3 credits · Undergraduate credit

This course aims to equip participants with the essential skills required for leveraging data science techniques for astrophysical research. Developing practical skills in academic software engineering practices are a key component of this course. Throughout this course, students will gain hands-on experience with research-specific Python libraries and master version control and code collaboration via GitHub. We will delve into the core principles of machine learning and identify the appropriate applications for various techniques, including unsupervised and supervised learning, regularization, and neural networks. Students will apply multiple machine learning techniques to astrophysically relevant datasets. We will also discuss the impact of applying data science and algorithms in society, to explore the roles and responsibilities of data scientists beyond the context of astrophysics. This course will use Python as the primary programming language.