Toby Hodges, Renato Alves (HD-HuB)
23/03/2020 - 24/03/2020
09:30 - 17:30
This course provides an introduction to programming with the Python language. The course material is suitable for complete beginners, with no previous programming experience or knowledge required or assumed. Participants can work through the course at their own pace, so the materials are also suitable for those with some programming experience.
Python has grown in recent years to become one of the most widely-used programming languages in biology. This increasing popularity reflects how easy Python is to learn compared with other languages, and how adaptable it is to a wide variety of different tasks. Simultaneously, the rise of data-driven approaches to science means that programming skills are becoming more and more important for biologists.
The course will include several short taught sections but most of the time will be devoted to more informal, practical sessions allowing attendees to get to grips with the language at their own pace. This provides the perfect starting point for scientists who would like to begin programming, while also catering to more experienced programmers who just want to learn the fundamentals of a new language.
Participants will learn:
- the basic concepts and building blocks of programming in Python
- how to quickly automate repetitive tasks and calculations
- the best ways of handling different types of data
- working with the extensive catalogue of subject-specific modules available for Python
- how to read data from a file, process, and summarise it
- automating the visualisation of data using Python’s powerful plotting libraries
After attending the course, you will have a good understanding of the core themes of programming, and be able to write your own Python programs, to automate repetitive analysis tasks.
We do not expect the participants to have prior knowledge of scripting. This is a course for the researchers who are interested in learning the automation of their tasks such as dealing with a large number of files to carry out identical or similar analysis using Python programming language.