×î×¼µÄÁùºÏ²ÊÂÛ̳

XClose

×î×¼µÄÁùºÏ²ÊÂÛ̳ Module Catalogue

Home
Menu

Mathematics for Natural Sciences B (NSCI0006)

Key information

Faculty
Faculty of Mathematical and Physical Sciences
Teaching department
Natural Sciences
Credit value
15
Restrictions
You do not need previous experience of using Python to take this module. A-level mathematics or equivalent is required. The module is designed for students taking the Natural Sciences programme, but other undergraduates are welcome. There may be limits on the number of students who can be accepted due to the constraints of class size. The module is not suitable for students who have already taken a first course in mathematics at undergraduate level, or if you require a high level of mathematical formality (e.g. physics).
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module provides an applied introduction to key mathematical modelling ideas and techniques used in scientific research. Content and examples are tailored towards students who study in subject areas including life sciences, earth sciences, chemistry, sustainability. You will study:

  • Python basics = Introduction to the Python programming language and computer methods.
  • Mathematical concepts = Elementary calculus and the link between continuous and discrete.
  • Analytic techniques = Methods for solving and analysing elementary differential equations
  • Modelling ideas = Visualising and interpreting flow

The module is taught through a combination of lectures and workshops. Students who complete this module should be able to:

[1] Understand Python code and write your own short programmes

[2] Investigate scientific problems with a combination of analytic and computer approaches

[3] Communicate mathematical content accurately and infer scientific conclusions

Module deliveries for 2024/25 academic year

Intended teaching term: Term 1 ÌýÌýÌý Undergraduate (FHEQ Level 4)

Teaching and assessment

Mode of study
In person
Methods of assessment
50% Coursework
50% In-class activity
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
72
Module leader
Dr Ella Metcalfe
Who to contact for more information
natsci@ucl.ac.uk

Last updated

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

Ìý