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The Programming part of this module aims to extend the students' programming skills and introduce them to advanced structured and object-oriented design concepts, providing the foundations for design and programming in any other environment.

On completion of this module, students will be able to:

• Use practical object-oriented Python programming skills to investigate and solve complex problems.
• Select and apply appropriate programming instructions, libraries, data structures and algorithms to model and solve complex problems using robust object-oriented code written in Python.
• Apply knowledge of mathematics, statistics and computer science principles to the solution of complex problems using Python libraries for maths, data science and machine learning.

The Control part of this module of the module represents an introduction to control systems and to the analysis of the behaviour of dynamical systems. This module provides a fundamental understanding of feedback control systems and dynamical systems in terms of steady-state response and stability; it enables the study of feedback control systems with Laplace, Nyquist and Bode plots.

On completion of this module, students will be able to:

• Comprehensively know the basic principles underlying control theory; know and distinguish the mathematical and computer models relevant to transfer function analysis and be able to apply them to real-world models for control systems.
• Know and explain the behaviour of linear systems.
• Know and apply stability criteria related to control systems based on the following diagrams and methods: Root Locus, Bode, Routh Hurwitz and Nyquist stability criteria; Design compensators.
• Know and apply mathematical modelling techniques pertinent to control systems.