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Introduction to Coding for Bioscience Research (Python) (BIOS0030)

Key information

Faculty
Faculty of Life Sciences
Teaching department
Division of Biosciences
Credit value
15
Restrictions
Students who have already taken or selected a similar module covering introductory coding in Python (e.g. NSCI0036) will not be accepted onto this module. No specific module prerequisites. Please contact the module organizer if you have any questions about the background required.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

Content:

Modern bioscience research increasingly makes use of computational methods to collect, explore, analyse, display and share data and results.

In this module students will learn the foundational skills of coding so that they can write computer programs and analyse data using the Python programming language.

Students will be taught using examples drawn from bioscience research, and apply computational techniques to a research question.

Module Aims and Objectives:

Upon successful completion of this module, students will:

- understand the fundamental concepts in programming

- be able to write computer programs in Python, including file I/O and simple algorithms

- be able to apply best practise in designing and structuring Python code

- know how to use Python to import, prepare, filter and manipulate experimental data sets

- be able to use computational approaches to explore and analyse data, being able to apply simple statistical tests and interpret the results

- be able to use Python plotting libraries to produce publication quality figures

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No prior programming experience is necessary.

Module organizers: Term 1 delivery: Dr Philip Lewis听; Term 2 delivery: Dr Alexander Fedorec.

Module deliveries for 2024/25 academic year

Intended teaching term: Term 2 听听听 Undergraduate (FHEQ Level 5)

Teaching and assessment

Mode of study
In Person
Methods of assessment
60% Exam
40% Dissertations, extended projects, and projects
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
39
Module leader
Dr Alexander Fedorec
Who to contact for more information
philip.lewis@ucl.ac.uk

Last updated

This module description was last updated on 19th August 2024.

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Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed timed assessments and in-class activity will be confirmed by the teaching department for the module.

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