Python Programming Courses

Below are the dates for the next courses that we are running in York. We can run either of these course on site if you have a group who would all like to learn Python.

Introduction to Python Programming

13-14 August 2019

This is a two day course aimed at getting those without previous programming experience to have enough confidence to start writing small scripts for doing routine data analysis tasks.  The course begins with an introduction to the Python language covering the main data types and the Python statements that can be used to manipulate them.  From there, we progress to reading and writing files and displaying graphs and charts.  The course is geared towards data analysis, but there will be time in the last session to explore how more specific problems (such as sequence analysis, manipulation of geospatial data, image handling or web programming) can be tackled in Python.

To register, please download an application form, complete it and e-mail to Marie Hughes.

Advanced Python for Data Analysis

15-16 August 2019

This course starts from where the Introduction to Python Programming ends, and introduces tools that can be used for handling the large data sets which are now so common in biological research.  The course looks at methods for interpreting the output of tools for methods such as RNA-Seq, genomics variant calling and GWAS, which allow you to select and filter the data and produce a range of visualisations using Python.  The course also covers the basics of object-oriented programming.

To register, please download the appropriate application form, complete it and e-mail to Marie Hughes.

Any queries about the content of the above courses, please contact course organiser Dr Peter Ashton 

Location:  Biology Department 

If you wish to register your interest please email .


Please see below some feedback from our recent course delegates: 

Introduction to Python Programming

"Why didn't I learn programming years ago?  I am strongly considering returning to take your advanced course."

"I am intending to immediately start experimenting with using what I have learnt to analyse my own research data.  What I have learnt has helped me see many places this could be useful that I didn't realise before."

"The pace is good as everyone can work at their own ability."

Python for Biological Data

"Challenging but well pitched for people who have done the introductory course."

"Very new to Python but more comfortable by the end and good to apply to actual sequence data."

"The clarification of object methods and attributes, as well as the Genome Diagram section - particularly useful for me."

"Very thorough course with hands-on assistance and responsive help."

"Good job by all - very supportive environment."