STUDY

Many organisations in many sectors have essentially become software houses with dedicated applications. Delivering value quickly, securely and reliably to customers is as vital to these companies as it is to software consultancies and giant technology firms (such as Google, Microsoft, Apple and Meta). DevOps, which is an evolution of agile development approaches, has become the key industrial practice to achieving these goals. DevOps combines Development and Operations to achieve a fast flow of planned work into production, where its successful implementation means fewer problems experienced by customers and faster fixes to those problems.

As a computing professional gains experience, opportunities will arise to move beyond the role of a competent team player and project contributor. This can involve taking on responsibilities such as becoming an engineering manager, leading a project, or both. These career progression paths are sometimes known as the Manager’s Path and the Staff Engineer’s Path. Both pathways require a strong grasp of soft skills and people skills, whether it's managing staff members or influencing others without formal authority. This module provides the soft and technical skills needed to support the long-term career progression of a computing professional.

Software engineering is the systematic, disciplined and quantifiable approach to the development, operation and maintenance of software. Over time, the scale and complexity of the problems addressed by software have increased with a corresponding increase in the scale and complexity of the software solutions. Such problems require the use of more advanced techniques in requirements engineering, software architectures, designing for specific attributes, advanced coding, and new testing practices. This module covers the full gamut of these techniques.

For many organisations, migrating applications and externally facing customer solutions to the cloud (AWS, Microsoft Azure, or Google Cloud) is part of their trajectory to controlling costs, adapting to change, and delivering services effectively and elastically with a global reach. This module explores cloud ecosystems, the drivers for cloud computing and when it is an appropriate solution. It provides practical skills in how to design and construct cloud solutions to deliver business needs. The resultant architectures will be secure (in terms of access to resources, workloads and applications), resilient (in terms of highly available, loosely coupled and/or fault-tolerant design choices), high-performing and scalable (in storage, compute, database and networking) and cost-optimised (in storage, compute, database and networking) and sustainable (energy efficient).

This module is designed to equip you with the essential knowledge and skills needed to excel in the critical field of cyber security. Throughout this module, you will gain an in-depth understanding of modern cryptographic techniques and explore robust network security protocols. The course emphasises practical skills development through virtual labs and real-world simulations of cyber-attacks and defences. Additionally, with the rapid proliferation of smart home technologies (Internet-of-Things - IoT) and advancements in cloud computing and machine learning, the need for robust security measures has never been more critical.

This module addresses the critical need for professionals skilled in cyber detection and forensic investigations. With a focus on the practical application of digital forensic tools, the legal and ethical aspects of investigations, and the methodologies for conducting thorough and responsible forensic investigations, ensures you gain the in-depth knowledge and skills necessary to excel in this critical field. A comprehensive exploration of digital forensic techniques, the tools used in the industry, and the legal frameworks governing forensic investigations. Upon completion, you will be well-equipped to conduct digital forensic investigations across various contexts, including criminal justice, corporate security, and civil litigation.

Artificial Intelligence (AI) includes many techniques for classification, analysis and prediction. This module aims to give you an appreciation of the types of application areas and problems that advanced AI techniques can enhance and optimise including artificial intelligence in business and financial applications, artificial intelligence in games, artificial intelligence in health sciences and medicine, and artificial intelligence in industrial control. This module covers both conventional AI techniques that have the advantage of being “explainable AI,” as well deep learning approaches which are very powerful techniques and are suitable for complex models.

This module introduces advanced topics in deep learning and how it can solve problems in many areas, such natural language processing, robotics, healthcare and computer vision etc. Neural networks are first reviewed and how training can be achieved with backpropagation. Various forms of advanced deep neural networks are developed, such as recurrent neural networks, transformers and deep reinforcement learning. Programming approaches are discussed for training and deploying neural networks. This module also covers implementations of many applications of deep learning in Natural Language Processing, Computer Vision and Robotics using Pytorch deep learning framework.

This module provides you with an opportunity to apply the knowledge and skills you have acquired so far from your course on a single significant technical project. It will require you to utilise practical, intellectual and decision-making skills in novel situations. The project will provide a mechanism for you to develop and demonstrate your autonomy and self-direction, whilst undertaking a problem-solving approach to a chosen topic.