Maths & Comp Methods for Complex Systems (817G5)
Mathematics and Computational Methods for Complex Systems
Module 817G5
Module details for 2022/23.
15 credits
FHEQ Level 7 (Masters)
Module Outline
This module provides a foundation in mathematical and scientific computing techniques used in various fields, including artificial intelligence, artificial life, data science, and computational neuroscience. The topics covered also provide the necessary theoretical grounding for modules such as Machine Learning and Adaptive Systems, as well as for the research projects for Artificial Intelligence and Adaptive Systems MSc and the Data Science MSc.
Topics include:
- Vectors and matrices
- Differential calculus
- Numerical integration
- Probability and hypothesis testing
- Dynamical systems theory
Pre-Requisite
MComp Computer Science. This module must be taken if G6078 Game Design and Development was taken in year 2.
MSc Computer Science (conversion). This is a pre-requisite for 934G5 Machine Learning
Module learning outcomes
Use vectors and matrices to simplify mathematical operations using Python.
Apply gradient descent for function optimisation using Python.
Construct and integrate simple mathematical systems and analyse their stability using dynamical systems theory.
Analyse a scientifc topic mathematically.
Type | Timing | Weighting |
---|---|---|
Coursework | 100.00% | |
Coursework components. Weighted as shown below. | ||
Problem Set | A1 Week 2 | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
Term | Method | Duration | Week pattern |
---|---|---|---|
Autumn Semester | Lecture | 2 hours | 11111111111 |
Autumn Semester | Seminar | 2 hours | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Dhruva Raman
Assess convenor
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