Program Overview

A postgraduate pathway is a single course comprising two stages of study; Pre-Master’s and Master’s. When you successfully complete the full pathway you will be awarded a Master’s degree from Anglia Ruskin University College

Advantage of Anglia Ruskin University College Postgraduate Pathway

The postgraduate pathway is designed for students from a variety of backgrounds who:

• Require additional English language training
• Come from a different academic environment to that of the UK
• Have been away from studies for a period of time
• Are looking to fine-tune skills already gained during undergraduate studies, employment or both

If you fall into any of the above categories, choosing the postgraduate pathway at Anglia Ruskin University College is the right decision.

The Pre-Master’s pathway will prepare you for future postgraduate studies by giving you confidence and expertise in areas relevant to your taught Master’s degree. You will:

• Develop your fundamental knowledge and understanding of the basic principles relevant to your chosen degree
• Develop basic numerical techniques, research methodologies and ICT, presentation and communication skills
• Gain a competent set of transferable skills that will help you in your academic studies and future career, and enable you to make informed decisions
• Attain the necessary level of language competence specific to your chosen field of study.

Pre-Master's (Stage 1)

Computing and digital technology overview

Our close links with the electronics, software, audio and creative industries mean we stay up to date with what your future employers need and ensure we’ll help you develop the skills and knowledge to become an expert in emerging and important technologies.
Improve your computer science expertise by developing industry level skills to design, develop and implement web solutions for clients worldwide. Specialise in cloud infrastructure within modern data centres, web application programming and IT security within business.
Take your computer game development skills to the next level. Study, plan, produce and test games in our specialist studios. Learn how to identify new and existing cyber threats and determine methods and processes to minimise attacks. Information technology (IT) is the application of computers and telecommunications equipment to store, retrieve, transmit and manipulate data.

Enhance your knowledge and expertise in computer science or electronics, and address the challenges in industry where machine learning techniques are being used increasingly in a wide number of applications. This course is supported by Intel’s AI Academy through their online and data processing resources.
Artificial intelligence and machine learning is a growing industry worldwide. Societies are adapting to the new technology landscape, becoming more flexible and also inheriting an attitude of lifelong learning, collaboration, innovation and entrepreneurship.

Using a range of skills from data science, to programming and hardware architectures that allow suitable artificial intelligence solutions to be produced and implemented, this course focuses on up-to-date theoretical and practical developments within machine learning, neural networks, signal processing and remote sensing and how these occur in the intelligent systems. It also allows you to become acquainted with current developments in artificial intelligence, and be able to apply yours skills in intelligent system design and development.

You will be trained in subjects that address the challenges of the current industry, studying modules that focus on data acquisition technologies and data processing techniques, including the development of AI systems, allowing you to become acquainted with digital signal processing, remote sensing and Internet of Things platforms, learning to program processors produced by ARM Ltd, a major player in the world of microelectronic component software/hardware design, based in Cambridge.

You will also explore neural networks and artificial networks, deep learning in Python using Scikit-learn, machine learning models and model evaluation using performance matrices, parametric and non-parametric algorithms or decision trees. Develop fundamental methods and algorithms that enable intelligent systems to interact with their environment through feedback, autonomously learn from data, and interconnect with each other to form collaborative networks, turning mathematical and theoretical insight into enhanced autonomy and performance of real-world physical systems. The practical skills gained help to prepare you for jobs related to intelligent systems and machine learning.