There's no escaping it - data analysis is an essential part of the scientist's toolkit. We are working with increasingly larger and more complex datasets. At the same time programming provides us with tools that can automate data analysis and make it easier for us all. Programming leverages both well established and state-of-the-art statistical and modelling methods, some of which are available as soon as a paper is published! From mining data lakes by automated analysis through to sharing data and statistical results with colleagues, programming is an essential data analysis skill for the modern biologist.
This hands-on, one-day course will teach you the basics of data exploration, analysis and visualisation using Python, a popular and powerful computer language, and the Jupyter Notebook environment.
This course is a natural follow on for those who have done the Programming for Biologists with Python course or with previous experience using Python (see prerequisites below
). If you are unsure whether you meet the pre-requesites, please get in touch
explaining your expereince and we can contact the course leaders. .
Who is the course for?
Biologists at any career stage in biology and related areas of science and medicine who have some experience of coding in Python (see prerequisites below) and wish to expand their skills in the area of data analysis and visualisation. Some statistics knowledge is assumed (see prerequisites below).
What does the course cover?
Data Exploration and Hypothesis Testing
In the ﬁrst part of the course we'll walk through our example datasets and introduce you to some key python modules for quick and easy data exploration. In groups we will clean our datasets, introducing data engineering approaches for repeatable analyses.
We will then explore common statistical hypothesis testing and identify the correct tests for our example datasets and hypotheses. We'll explore different python modules for these tests and use them on our example datasets. As part of this section we will demonstrate generalised linear models.
Visualisation, Reproducibility and Sharing
In the second part, we'll focus on visualising data by building interactive visualisations for data exploration and to illustrate the results of our earlier hypothesis testing. We'll then discuss different aspects of reproducibility and of sharing data, code and results. Finally, we'll package up the day's activities in an easy-to-share format that colleagues without coding experience can run/use as interactive widgets to see your results.
A Note of Prerequisites
We expect attendees to have previous Python skills equivalent to having done our ‘Programming for Biologists' course and built upon those skills after the course. This means that participants should be comfortable:
● Installing applications and python modules on their own laptops
● Reading and writing data into pandas dataframes
● Manipulating pandas dataframes to filter data
● Using numpy, scipy and pandas for simple data analysis, e.g. calculating mean or running
● Using seaborn and matplotlib for visualising data
If you are unsure whether you meet the pre-requesites, please get in touch
explaining your expereince and we can contact the course leaders.
This is a one-day, in-person course covering a lot of material. The day will include short theory talks (programming and data analysis concepts, techniques and examples) combined with practical exercises using real-world datasets.
Attendees will be working on their own laptops and will be expected to install some programmes and python modules before the course. Any laptop or operating system is suitable.
Who are the course tutors?
Dr Chas Nelson is Chief Technical Officer and Founder of gliff.ai, a company offering secure,
easy-to-use, low-code/no-code software for biomedical artificial intelligence. Before that Chas was a Research Fellow at the University of Glasgow working in bioimage analysis and a Consultant Data Scientist for Fjelltopp Ltd working on public health challenges. He has taught computer science topics to a wide variety of groups and comes prepared with an undergraduate degree in biology (and physics) and a PhD in computer science, speciﬁcally bioimage informatics. Python has long been Chas' favourite language and Chas' teaching interests are in building courses that enable participants to go on and continue learning after the course.
Mikolaj (Miks) Kundegorski is a technical advisor specialising in health information systems.His background spans from physics to computer vision and he is currently working towards his PhD in modelling of collective animal behaviour at the University of Glasgow, where he continues to use Machine Learning to aid academic research.He has been using Python for many years to solve real-life problems and bring technological improvements in places that need it most by working for the World Health Organization, Food and Agriculture Organization of the United Nations, and his company Fjelltopp Ltd.
Between them, Chas and Miks will be able to fully support your learning throughout the day and provide you with the tools to continue developing your skills after the course.
Continuing Professional Development (CPD)
A certificate of attendance will be provided after the event.
We evaluate all of our training events, to make sure that we maintain a high quality of training.
This event has been approved by the Royal Society of Biology for purposes of CPD
and can be counted as 24 CPD points
Members - £150 + VAT
Members of Member Organisations, SCAS members - £260 + VAT
Non-members - £300 + VAT
Non-members who have completed a membership application and made payment can also benefit from the discounted member rate.
For further information about the course please contact Francesca Chantry, training and registers officer at firstname.lastname@example.org
or on 020 3925 3457.
RefundsUnfortunately, the Royal Society of Biology is unable to offer refunds on training courses that have been attended. We do, of course, welcome and encourage any feedback from a course and will continue to improve the service we offer.
Terms and Conditions
By booking to attend this event, you are confirming you have agreed to the RSB's Terms and Conditions which can be found here