Outline:

This module provides an introduction to basic specialist skills required by the practicing astrophysicist. This is achieved through a range of observations and experiments based at UCLO, together with development of numerical methods, data analysis and the Python programming language.

Aims:

All practical and computing modules within the Department contribute to a continuing development of students’ scientific, technical and transferable skills, extending throughout their degree programmes. Collectively, these modules have the overall aim of equipping the student with those practical skills which employers expect to find in physics-related graduates, whether they are employed in scientific research or development, or in a wider context. PHAS0020 aims to build on and extend the practical, observational, analytical and computer skills acquired in the first-year practical courses.

Teaching and Learning Methodology:

In the computing sessions, students will work individually with python-based tools to familiarize with a wide range of data analysis and statistical tools, which they will subsequently put to use with a range of astronomical programs and libraries. Sessions are designed to provide a tool hand-over element where students learn to use specific data analysis tools through the use of python code and a subsequent application element where students combine their incremental coding language with each session-tool to expand and apply this to a different range of astronomical problems.

In the practical sessions, students work by following prescriptive scripts. Great emphasis is placed on the formation of good habits in the keeping of a laboratory notebook for which students are given detailed advice. Demonstrators not only help students understand experiments and observations and overcome difficulties as they arise, but also inspect student notebooks to provide instant correctives to any bad practice arising. The course will be run from the UCL Observatory.

Self-study: In addition to timetabled hours it is expected that you engage in self-study in order to master the material. This can take the form of studying the material, practicing problem questions, preparing for laboratory sessions, writing up reports and further reading in textbooks and online.