An essential skill for postgraduate students is the ability to investigate topics with the objective of identifying facts , theories, ideas, methodologies, etc., that could inform the development of new insight for further research.  A major aspect of this is critical analysis of information. The module aims to develop critical reasoning in students and an understanding of other researchers’ work.  Students will learn how to use current research literature and relevant sources to gain new insight for a new research.  They will learn how to support their research report with relevant facts, theories, ideas, etc.  They will develop their ability to understand approaches and methodologies adopted in existing research toward writing a literature review and handling full research projects in their subject area.

The learning content also includes:

• Time management, library skills and literature search
• Evaluation of information sources
• Ethical issues in science, technology and engineering research (including intellectual property and plagiarism)
• Writing for research: styles and rules for presentation (including referencing standards)
• Choosing a research area and evaluating source material
• Hypothesis formation
• Design and application of questionnaires & interviews
• Quantitative and statistical tools for researchers (e.g. R, Python, SPSS)

The Robotics module provides an introduction to the foundational principles of robotics, exploring the theoretical aspects that underpin the design, application, and ethical considerations of robotic systems.

You will begin by examining the fundamental question: What is a robot? This includes understanding the diverse applications of robots across industries and their role in society. The module also delves into the ethical implications of robotics, such as their impact on employment, privacy, and safety.

Key technical topics include an overview of mechatronics, which integrates mechanical, electronic, and computer engineering; sensors, which enable robots to perceive their environment; and control systems, which ensure robots can perform tasks accurately and autonomously.

This module investigates different types of machine learning algorithms to find patterns in data. Each algorithm will be discussed in theory and practice, discussing: its data pre-processing requirements, pseudo-code, and evaluation metrics, e.g., Dunn index for clustering. Detailed demonstrations will show how to apply these algorithms to data using specified libraries in Python. Students will be required to investigate the merits of each algorithm for various types of data in both theory and practice.

This module investigates tools and techniques to extract, transform and load (ETL) data for further analyses or analytical processing (OLAP). Students will be guided step-by-step through the ETL process using Python, API's and SQL to show visualisation and analysis. The module will also discuss the ethical implications of data, data processing, laws and standards. 

The databases and security module involves the development of databases and their querying through the use of SQL. Databases will be discussed both theoretically and in practice. Students will have opportunies to develop and practice database creation and development. Database security will be discussed and shown how to apply in practice.

This module covers the related topics of computational complexity, optimisation and algorithm design in depth and detail. Learners will become familiar with the concepts and techniques required to classify problems and develop the ability to apply associated algorithmic approaches wherever possible. Some of the most important open questions in computer science will be addressed both from a theoretical and practical context.

The Research Project is the pinnacle of a taught, academic programme of master’s level study. It is a demonstration of academic, subject-specific, and research capabilities. Projects are a significant and substantial piece of individual work that draw upon the knowledge, technical abilities, and problem-solving skills developed in earlier modules. Students need to apply high-level research skills to a defined, complex problem. A distinguishing feature of the research project is that it is largely self-directed and independent, with support from an academic supervisor.