MSc Artificial Intelligence and Robotics with Advanced Project

University of Hertfordshire

In this module, you will work in teams to design, construct, program and test a robotics platform in a virtual environment. Furthermore, you will learn about Human-Robot Interaction and the current state-of-the-art linking research to teaching. Skills that will be developed on this module include CAD, modelling, robot control (control systems design and programming) and knowledge of Human-Robot Interaction research. This is a practical, hands-on module designed to replicate real-world challenges in a simulated environment.

The project module includes both a taught and a non-taught component. During the taught part, you will cover the following topics: Project plan development, Project risk assessment, Ethics and working with human participants, Problem analysis and decision-making, Literature review, Conducting investigative work, Documenting a project, and Report writing and presentation. In the non-taught part, under the guidance of a supervisory team, through a series of scheduled meetings lasting up to 6 hours, you will work towards completing a project in Artificial Intelligence and Robotics.

In this module, you will take a deep dive into the dynamic field of robotics, focusing on the design, simulation, and implementation of robotic systems. You will explore key concepts such as robotic kinematics, dynamics, sensor integration, and advanced programming. Practical sessions in simulation environments will complement your theoretical knowledge, preparing you for complex tasks like navigation and autonomous manipulation. Emphasis will be placed on both the intellectual and practical aspects of robotics, ensuring you are well-prepared for advancing technology in industrial applications.

In this module, you will explore legal, social, ethical, and professional issues that may affect the work of practitioners in the computing and technology sectors. You will focus on the ethical considerations inherent in the development of responsible technologies. The topics covered will vary from year to year to reflect contemporary research and issues.

In this module, you will study a selection of research topics centred around neural network theory and design, Machine Learning, including supervised and unsupervised learning, and some interesting applications such as data mining, biocomputation, evolutionary algorithms, neural networks as models of brain function in health, disease and development, and data visualisation. The actual topics taught may vary from year to year.

This module provides preparation for the MSc Project. The module covers: Defining and gauging the suitability of a personal project to address a complex problem; Setting individual targets and goals relevant to the undertaking of the project; Determining ethical, professional and social considerations related to project design, implementation and delivery; Developing self-evaluation skills to support self-analysis of learning, skill acquisition and performance; Understanding particular models and methods used to initiate, plan, report on and manage complex technical projects.

This module has two delivery elements. For the taught element, you will learn how to build and manage strong teams, foster communication and trust, understand the intricacies of large-scale projects, understand project management methodologies and tools, set up and structure activities that run in parallel, and manage change requests from different stakeholders. For the project element, you will operate within a secure, semi-structured environment, participating in teams and working towards the completion of a large-scale, complex, and multidisciplinary project.

In this module, you will develop your theoretical, professional, technical, and academic skills to help you succeed in various data engineering contexts. You will take a practical approach to converting raw data into valuable knowledge. Working in teams, you will apply skills in cloud computing, big data, Machine Learning, and data visualisation, among others.

In this module, you will gain an in-depth understanding of a range of ideas, theories, and techniques used to construct Artificial Intelligence systems. You will focus on evaluating AI systems for tasks such as intelligent modelling, problem-solving, learning, decision-making, reasoning, agent or robot control, and more. You will also develop hands-on experience in designing and evaluating AI models tailored to address specific scenarios.