You will use industry-standard tools and techniques in this module, to design, implement, test and document simple programs using a current procedural language such as Python or C#. The module delivers the principal concepts of high-level programming, emphasises good programming practice and supports the techniques required to develop software which is robust, secure, usable and maintainable. The skills you develop will be directly transferable to the workplace.
This module will introduce you to structured relational development techniques involving the systems development lifecycle concept. Included are, requirements analysis, design methodologies and implementation of a relational database solution with SQL queries to meet a specified user need.
This module introduces you to the components present in modern computer systems and networks. On completing this module, you will be able to specify, construct and maintain networked computer systems, and gain an in-depth understanding of common network architectures, their function, and confidently solve their problems. This module makes use of the content, labs and assessment from Cisco Introduction to Networks, the first in the three course Cisco Accreditation (CCNA) series, which can optionally be continued at level 5 on the Advanced Network Switching and Routing module. Upon completion of this module, you may opt to undertake the associated CCNA exam.
This module provides an introduction to developing web sites using HTML/CSS. There is a focus on design techniques as well as client and server-side development using frameworks such as Angular.JS and Bootstrap. During the course of this module, you will create a complete website solution based on a small-scale scenario.
Entering third level education is exciting; but it can also be a daunting experience. At ARU, we want all students to make the most of the opportunities Higher Education provides, so they reach their potential, become lifelong learners and find fulfilling careers. However, we appreciate that the shift from secondary education, or a return to formal education is, in itself, quite a journey. This module is designed to ease that transition. You will be enrolled on it as soon as you receive an offer from ARU so you can begin to learn about university life before your course starts. Through Into ARU, you will explore a virtual land modelled around ARU values: Courage, Innovation, Community, Integrity, Responsibility, and Ambition. This innovative module is designed as a game, where students collect knowledge and various complete mini tasks. You will proceed at your own pace, though we expect all students to have completed their Into ARU exploration by week 6. Students who, for whatever reason, are unable to complete by that date, will be signposted to existing services so that we can be confident that they are supported.
View the full module definitionThis module will give you an insight into big data analytics and equip you with the necessary skills to exploit big data tools and methods to drive innovation and growth in modern global organisations and society. You will learn statistical methods and computing technologies used for big data. This module will help you understand various challenges linked to big datasets and equip you with the knowledge and tools to effectively use data for machine learning purposes. In addition to theoretical concepts, you will have hands-on experience with various datasets and tools for data preparation, analysis, visualisation and modelling. This module will give you the knowledge and understanding to help you work towards a career in data analytics. You will learn through a combination of formal lectures and tutor-led tutorials with independent study. You will develop key analytical and problem-solving skills, and will gain an aptitude for research, academic writing, and time management.
This module will enable you to reflect on what it is to be an IT Professional. Looking at both ethical and professional issues, the module will investigate the role that the IT Professional plays within organisations. You will consider managerial decisions, commercial aspects of IT decision-making, law in engineering, marketing, entrepreneurship, project management and project risk management using a number of case studies.
This module will build on the programming techniques learnt through Levels 4 and 5 and introduce you to a range of contemporary machine learning techniques, their principles, characteristics, and applications to real-world problems, and how to select, apply and evaluate solutions based on these techniques using the state-of-the-art software tools. You will also develop an understanding of the ethical and social implications of machine learning.
The aim of this module is to offer you an opportunity to demonstrate the skills required for managing and implementing a project. They will undertake a live brief, set by industry partners and carry out and execute a computing project which meets appropriate aims and objectives. On successful completion of this module you will have the confidence to engage in decision-making, problem-solving and research activities using project management skills. They will have the fundamental knowledge and skills to enable you to investigate and examine relevant computing concepts within a work-related context, determine appropriate outcomes, decisions or solutions and present evidence to various stakeholders in an acceptable and understandable format. You will work in development teams made up of members made up of a mix of students from across the 5 specialisms, ensuring that the live brief is appropriate to the skill sets represented.
Design patterns and algorithms are commonly defined as reusable solutions to commonly occurring problems within software design. The knowledge of modern design patterns has become a key requirement for the employment of software engineering graduates, therefore contemporary real-world scenarios will be utilised throughout the module ensuring currency of knowledge.
Ruskin Modules are a great opportunity to explore challenges and ideas outside your area of study. Working with students from a range of courses, you'll be supported to create meaningful connections across disciplines, and apply new knowledge to tackle complex problems and key challenges. Ruskin Modules are designed to grow your confidence, realise your potential and help you prepare for the world of work.
This module will introduce you to various data mining concepts and technologies. You will gain practical and applied knowledge of how to conduct data mining activities. This includes key concepts in data mining as well as the statistical and modelling techniques necessary to analyse and visualise large data sets to generate meaningful intelligence.
This module encourages you to consider future technologies and to consider developments in your field of choice. The aim of the module is to enhance your understanding of the current state, terminology, advantages, disadvantages, potential impact, and benefits of future technologies. On successful completion of this module you will be able to explain some of the most promising and impactful future technology and developments in computing. As a result, you will develop skills such as communication literacy, design thinking, employability, research, critical thinking, analysis, reasoning, interpretation and computer software literacy, which are crucial for gaining employment and developing academic competence.
This module provides a broad and rigorous introduction on data analytics and machine learning using graph. You will start with learning graph theories and basic concepts, followed by various graph algorithms, graph analytics and learning approaches. You will explore various types of machine learning based on graph, including graph representation learning and graph neural networks. Large scale complex data can be represented as a graph of objects and interdependencies between those objects. Such networks can be used to model various types of complex problems and challenges ranged from social networks to biological systems. Machine learning applications such as image classification, object detection, machine translation and speech recognition have been progressed and extended with Deep Learning and neural networks such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). However, Deep Learning can only be efficient to discover hidden patterns for Euclidean data (like text, images, and videos). Non-Euclidean data that are described by graphs can be processed using a specific class of deep learning that is called Graph Neural Networks (GNN). You will acquire the essential knowledge and skills to enable you to model complex real-world problems as graphs and get insights through applying various graph learning and analytics. The module includes both theoretical concepts and hands-on practical experiences, while it covers latest research works in graph analytics and learning.
This module will build on the programming techniques learnt through Level 4 and 5 and introduce you to the theory behind and creation of neural networks. You will be introduced to artificial neural networks and will gain an understanding of the important computational you network architecture and methodology. Building on the L5 module, Machine Learning Fundamentals, by the end of the module you will appreciate the difference between machine learning and deep learning, together with the tools and data requirements.
The individual Final Project module will allow you to engage in a substantial piece of individual research and / or product development work, focused on a topic relevant to your specific discipline. Your topic may be drawn from a variety of sources including: Anglia Ruskin research groups, previous / current work experience, your company in which you are currently employed, an Anglia Ruskin staff-suggested topic or a topic of your specific interest related to your course discipline. Your project topic will be appraised for suitability to ensure there is sufficient academic challenge and that satisfactory supervision by an academic member of staff is available. Your chosen topic will require you to identify / formulate problems and issues, conduct literature reviews, evaluate information, investigate and adopt suitable development methodologies, determine solutions, develop hardware, software and/or media artefacts as appropriate, process data, and critically appraise and present your findings using a variety of media. Regular meetings with your project supervisor will take place to ensure the project is closely monitored and guided in the right direction. A successful project will increase your employability as employers often place far more emphasis than the credit weighting suggests for this module because it will reflect skills directly applicable to the workplace and real world projects (such as qualities of self-management, planning and organisational skills). It is common practice at interview for an employer to ask you about your project as it gives you a chance to demonstrate your technical and communication skills on a specialist topic that you will be enthusiastic and knowledgeable about. For these reasons you will also have to undertake a small amount of Personal Development Planning with respect not only to your project but also more generally to prepare you for life after university.
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