MSc Applied Artificial Intelligence - 2 Years

London South Bank University

The pervasive nature of visual tasks in everyday life, and the amount of imaging information accrued by mobile, wearable and classical devices, calls more and more for sophisticated tools able to relieve the burden of image scanning and screening from human users. Additionally, many task can benefit from image-guided augmented reality scenarios (e.g. surgery), or can be automated through visual-guidance (robotics).

Data Management and Data Quality are increasingly at the heart of every commercial and research enterprise, as the value of data increases along with the need for adaptive security. This module will give you a critical and evaluative knowledge of the theory, practice and research of software engineering techniques for Data Management amid today?s complex and changing business/commercial/research environments.

The module introduces you to the basic theory, concepts, and techniques of data mining, and its role in data science and business intelligence. It will cover the main topics in the area. The module also focuses on developing practical skills in solving real-world data mining problems by using appropriate software suites. Base SAS, SAS Enterprise Miner, SAS Enterprise Guide and Tableau may be taught and used for this purpose.

The module introduces neural networks and deep learning, one of the key topics in modern applied AI.

The module requires students to undertake an independent piece of research/development work, investigating in depth a subject, in which they have a particular interest and of their own selection. The dissertation assesses students? ability to integrate information from various sources, to conduct an in-depth investigation, where necessary specify, appropriately develop bespoke software/technology-based solutions, to critically analyse results and information obtained and to propose improvements/further work. Each student will submit a dissertation of between 12,000-15,000 words.

The module will provide students with the critical skills, knowledge and analytical abilities needed to identify and address ethical challenges as they arise in practice from the application of AI. The module will engage with the ethical and societal challenges of AI and is thoroughly informed by the knowledge, theories and methods of established academic disciplines from philosophy to computer science.

This module will cover the fundamental concepts and techniques from linear algebra, differential calculus and probability.

Future Internet technologies comprise set of enablers to deal with the limitation of the existing Internet. This includes but not limited All-IP Networking Architectures, the evolution towards 4G+/5G networking architectures, open-based networking technologies, Cloud Computing challenges and IoT technologies and its interworking with 4G+/5G networks. The module will provide both theoretical knowledge and practical exposure to the students.

Industrial Cyber-Physical Systems (ICPS) are real-world networked industrial production systems having a cyber-representation through the digitalisation of data and information across the enterprise and value chain. This module offers a comprehensive overview of ICPS and outlines the challenges related to the fourth industrial revolution commonly referred to as Industry 4.0. The module consists of two parts. The first part will introduce the theoretical framework and supporting technologies of the fourth industrial revolution (e.g., industrial internet-of-things, digital twins, etc.). The second part focuses on system design and implementation aspects of ICPS along with multiple tutoring sessions.

The module introduces you to the basic theory, concepts, and techniques of machine learning using Python. It will cover the main topics and essential theory in the area. The module also focuses on developing practical skills in designing and developing machine learning systems using suitable software and algorithms in order to solve real-world problems.

The module covers theoretical and practical aspects of Natural Language Processing to design, develop and implement Collaborative and Cognitive Communication Systems for robotics while linking AI and NLP to human psychology patterns and applying it to Chabot?s, digital assistants and context-aware personalized interfaces. The lecture sessions will deliver state-of-the-art theories, models and algorithms covering neural Language models, speech tagging, Vector Semantics and Embedding, information extraction and sentimental analysis. The lab sessions will deliver hands-on practical sessions using Chabot frameworks, Python NLP libraries and tool kits for NLP.

This module provides an intensive introduction to programming, especially for students without a computer science background.

The module provides students with the ability to discuss, evaluate and use a variety of research methods and techniques for their chosen subject area of Computer Science and Informatics and to develop a professional and ethical approach to carrying out research-based projects. It also equips students with entrepreneurial and innovation skills increasingly sought by industry and employers.

The module introduces students to the basic elements and principles of robotics. Essential geometric concepts of rigid-body displacements will be introduced and applied to the kinematic analysis of different machines. Differential kinematics will be developed and applied to study the statics and dynamics of robots.Some problems concerned with the control of these machines will be considered.