Computer Science BSc (Hons)

Honours Degree , Full-time

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Key Details

  • 3 Years
  • 104 Typical UCAS Tariff
  • G400 Course Code
  • Full Time
female students on computer

Overview

Creativity and problem-solving are placed at the heart of the BSc (Hons) Computer Science course.   On the course, you will be given the opportunity to examine key themes such as computer networks and security, data science, embedded systems, robotics, software engineering, and user interface design and development. The course has an elegant blend of theory and practice and offers a stimulating and challenging learning experience that allows you to develop an informed and practical understanding of the study of Computer Science.

Why study Computer Science?

  • This course enables students to develop competence in Computer Science alongside wisdom in its application sufficient for them to progress to postgraduate study or employability.
  • Through applied modules, students are provided with a rigorous, coherent and engaging curriculum that draws on the teaching strengths and research expertise in the subject area.
  • Relevant professional bodies (e.g. British Computing Society) inform the learning experiences provided to acquire and develop the practical skills essential within Computer Science.
  • Learning opportunities encourage and support the spirit of intellectual curiosity and enquiry, an ability to apply computational thinking to solve problems and the capacity for creative computing.
  • Students develop an appreciation of legal, professional, economic, environmental, moral and ethical issues involved with Computer Science and their impact upon society.

What does the course cover?

In your first year, you will study the basics of computer science.   More specifically, you will use client-server architecture appropriately and study the security implications. You will analyse small-scale problems and design their solutions by applying algorithmic and mathematical techniques. The creation and manipulation of simple data collections, web development and programing would also feature in the foundation year.

 

In your second year, you tailor your study to your strengths while developing a deeper understanding of user interface design, robotics and cybersecurity. More so, you will demonstrate professional responsibility in the development of medium-scale projects.  You will have the opportunity to undertake a work placement, which will provide you with valuable and exciting experience within an area you may be considering for a career.

 

As you progress into the third year, you will study some of the important and higher level Computer Science modules that include topics such as Internet of Things, Deep Learning, Web Application Development and Game Design and Development.  Each of these modules develop your ability to think and analyse critically, and also to reflect and develop both personally and professionally with the aim of considering the role and career which you wish to undertake when you graduate. You will undertake a dissertation or final year project which will allow you to explore an aspect of Computer Science in greater detail.

How will I be assessed?

You will be taught through a combination of lectures, workshops, seminars, and practical sessions.  Modules are assessed through video papers, digital artefacts, e-portfolios and blogs alongside more traditional assessment types such as academic essays, presentations and projects.

What careers could I consider?

As a Newman Computer Science graduate, who has developed a passion for Computer Science, you will be well prepared for post-graduate study, professional training and graduate employment in the commercial sector.  You may choose to pursue a career as a software engineer, business analyst, network manager, web developer or games designer.   The course also provides progression to the PGCE Secondary Computing course at Newman as part of a seamless transition if you meet the Department of Education Initial Teacher Training entry requirements.

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Entry Requirements

You must achieve at least 104 UCAS points including a minimum of CC at A level or equivalent (e.g.MM at BTEC Diploma; MPP at BTEC Extended Diploma) towards the total tariff.

As it is not possible to achieve 104 UCAS points through an Access course, Access Students will need 106 UCAS points. You can reach this with the following combination of Distinction, Merit and/ or Pass grades at level 3 achieved from a completed Access course:  D27-M0-P18; D124-M6-P15; D21-M12-P12; D18-M18-P9; D15-M24-P6; D12-M24-P3; D9-M36-P0.

Five GCSEs at grade 4 (or C) or above (or recognised equivalents), including Maths and English Language, are also required.

Contact details

Contact for admissions enquiries:
Tel: 0121 476 1181 (Ext. 2386)
Email: admissions@newman.ac.uk

Contact for course specific enquiries:
Andrew Csizmadia,
Senior Lecturer in Computer Science Education
Tel:  0121 476 1181 (Ext. 2389)
Email:  a.p.csizmadia@newman.ac.uk

Course Fees

Fees per academic year:
Full-time Home/EU students: £9,250 *

Fees shown are for 2019/20 academic year. The University will review tuition fees and increase fees in line with any inflationary uplift as determined by the UK Government, if permitted by law or government policy, on enrolment and in subsequent years of your course. It is anticipated that such increases would be linked to RPI (the Retail Price Index excluding mortgage interest payments).

Additional costs:

 

Additional Information

General Academic Regulations: Terms and Conditions for students attending our courses

Course Modules

Optional Modules: find out how the University deals with changes that may occur in some eventualities

Timetables: find out when information is available to students

 

 

 

 

 

 

 

Modules

  1. DEVELOPING AS A COMPUTER SCIENTIST
    (Compulsory) cmu401
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    MODULE SUMMARY :

    In this module, students will develop an understanding of the ethical, professional and legal issues relating to computer science.  Students will develop critical investigative skills in applying ethical theories to technological outcomes vis-à-vis software engineering, cyber security and digital forensics. This module will provide students with the opportunity to identify and reflect on their strengths and weaknesses and to consider requirements for their future career in computer science.   They will develop their understanding of a range of computer science sources and evaluate their reliability and validity. Students will participate in critical reading, writing and develop their referencing techniques.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to:

    • present the knowledge, practices and fundamental literacies of computer scientist

    • develop problem solving skills needed to design and develop computational artefacts effectively

    • develop the ability to evaluate and interpret computational concepts, practices and perspective across disciplines, contexts and settings.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • identify and research key roles within relevant sectors of the creative industries

    • review and evaluate a range of communication and professional skills relevant to working in computer science settings

    • communicate underpinning knowledge and applied practice of audio, image and video manipulation relevant to the computer scientist

    • investigate the role of computers and the social, ethical and legal implications of digitisation

    • develop problem-solving skills, techniques and knowledge to elicit, analyse and specify requirements for computer systems.

    METHOD OF ASSESSMENT :

    Component 1 - 100% ePortfolio (2000 word equivalent)

  2. MATHEMATICS FOR A COMPUTER SCIENTIST
    (Compulsory) cmu402
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    MODULE SUMMARY :

    This module covers the fundamental discrete mathematics required by a computer science student in order to model and analyse the problems that arise in computer science. It lays the foundations for students to successfully complete the remainder of their studies as well as for a computing career.

    Vectors and matrices are the mathematical models underlying computer graphics, machine learning and deep learning. Logic is a tool used to reason about computer programs as well as the real world. Recursion is an important programming principle that comes with an associated proof rule, and other mathematical notations such as functions and relations are used routinely in computer science. Theoretical computer science can be considered an area of mathematics, and this module provides an introduction to the fundamental notions of this area.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • reinforce the concept of mathematics proof, including constructive proof by giving an algorithm

    • lay the foundations in discrete mathematics commonly required in many areas of computer science

    • present mathematical notations relevant to computer science and their applications

    • communicate and evaluate how abstraction allows the formulation and proof of properties for real-world and computational phenomena, and enable students to apply this technique

    • provide an understanding of and practice in the fundamental notational of proof

    • provide students with sufficient mathematical knowledge to enable them to interpret the foundation of their subject for both academic purposes and career development

    • introduce students to the language and methods of professional mathematics.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • investigate the fundamental notations from logic, discrete structures and mathematics and their relevance to computer science

    • comprehend a mathematical proof

    • appreciate mathematical notation

    • use mathematical notation and formalise general arguments

    • reason with and apply methods of mathematical proof to practical scenarios

    • apply methods and techniques from logic, discrete structures and mathematics to analyse questions from computer science and devise approaches to solve problems.

    METHOD OF ASSESSMENT :

    Component 1 - 30% Examination (2 hours, 600 word equivalent)

    Component 2 - 70% Workbook (1400 word equivalent)

  3. COMPUTER ARCHITECTURE AND NETWORKING FUNDAMENTALS
    (Compulsory) cmu403
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    MODULE SUMMARY :

    This module will introduce students to concepts involved in the fundamentals of computer architecture, operating systems and networking. The emphasis is on the hardware aspect of a system, and how hardware is used during the execution of software.

     

    In this module, students develop the knowledge, skills and understanding required to comprehend computer systems, be they terminology, models, methodologies, structures, number representation and a general introduction to basic computer systems. Knowledge of fundamentals of computer architecture is becoming increasingly important in business and finance, and are applicable to problems which have been considered mainstream computing.

     

    An operating system is typically the lowest layer of software in a computer. It provides an abstracted interface so that applications can run on diverse hardware without modification and it provides security which prevents misbehaving software from ‘crashing’ the hardware or disturbing other tasks which may be running simultaneously. This module provides an introduction to the major principles of implementing an operating system.

     

    Network fundamentals cover network architecture, structure and functions. It introduces the principles and structures of Internet Protocol (IP) addressing, fundamentals of Ethernet concepts, media and operations.

     

    This module aims to serve as an essential foundation for further studies in the single honours Computer Science degree programme.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • interpret both the theoretical and design concepts which underpin computer architecture

    • communicate both the theoretical and design concepts which underpin operating systems

    • develop the ability to evaluate and interpret the theoretical and design concepts which underpin the fundamentals of network systems.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to:

    • interpret the basic Von Neumann/imperative computational model

    • investigate the binary nature of digital computers, and how bit patterns can be used to represent information such as characters, numbers and instructions

    • explore the basics of assembly language programs

    • investigate the overall structure and functionality of a modern operating system and its interactions with the underlying computer hardware and overlying user-program

    • gain awareness of the operation of the components of an operating system, i.e. the I/O device manager, the memory manager, the process manager, the file manager

    • apply the fundamentals of network systems: architecture, structure, functions; IP addressing and Ethernet concepts with a predetermined scenario.

    METHOD OF ASSESSMENT :

    Component 1 - 70% Portfolio (1400 word equivalent)

    Component 2 - 30% Group Presentation (600 word equivalent)

  4. PROGRAMMING FOR A COMPUTER SCIENTIST
    (Compulsory) cmu404
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    MODULE SUMMARY :

    This module provides the first exposure to programming in this undergraduate degree programme, and for some students their first encounter with programming at all. It traduces problem-solving and structured procedural and object-orientated programming.

    In the first half of the module, students are introduced to the components and constructs of procedural programming. Emphasis is placed on designing, developing and deploying correct, efficient, maintainable and scalable programs. 

    The second half of the module provides students with a thorough introduction to computer data structures and algorithms in the context of object-orientated programming. The construction of well-designed interfaces, program encapsulation and abstraction are discussed. 

    The focus of this module is on developing knowledge, skills and understanding as they demonstrate mastery of software development. The module is based on several example programs and emphasis is placed on practical work with the aim of ensuring that theory covered in lectures is reinforced by practical programming tasks.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • present the concepts of procedural programming (i.e. sequence, selection, iteration, functions, recursion) and manipulation of simple data structures (i.e. variables, arrays, files)

    • explore the fundamental computing data structures allowing the representation of data within a computer program.

    • introduce the fundamentals of programming from specification to implementation and testing

    • apply object-orientated programming concepts

    • embed the principles of program analysis and design: specification, error handling and approaches to testing programs.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • apply programming constructs and principles of programming to solve a series of problems

    • design, develop and deploy programs to solve a specified problem

    • test and debug programs

    • review and evaluate informal justifications for the programs they design

    • investigate alternative methods for documenting the design process

    • communicate the need for a development process.

    METHOD OF ASSESSMENT :

    Component 1 - 60% Workbook (1200 word equivalent)

    Component 2 - 40% Project (800 word equivalent)

  5. DATABASE DEVELOPMENT
    (Compulsory) cmu405
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    MODULE SUMMARY :

    The module will give students the opportunity to learn the fundamentals of database design. They will investigate the structure of data within a relational database, interact with, and protect the data within the database.  Students will develop practical experience of problem analysis, especially concept data modelling, relational theory and relational algebra.  Students will develop database implementation skills for optimisation using structured data, held in relational databases, accessed via SQL and explore the data storage requirements of on-line businesses, companies and organisations.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • develop the ability to design and implement Relational Database Management Systems (RDBMS)

    • develop problem solving skills to understand Structured Query Language (SQL), Data Definition Language (DDL) and Data Manipulation Language (DML).

    • provide an understanding of relational models and develop an awareness of relational algebra

    • develop knowledge of concurrency control, database recovery and back up procedures

    • explore the concepts of Distributed Database Systems, Middleware, data warehousing, Online Analytical Processing (OLAP), Model Driven Architecture (MDA) and other database models and trends.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • evaluate the various types of database models available and be able to apply to relevant operations

    • examine and interpret how databases are designed, organised and managed

    • demonstrate competence in the use of databases, DBMS and SQL

    • write and manipulate efficient SQL code to problem solve and return data from database objects.

    METHOD OF ASSESSMENT :

    Component 1 - 60% Project (1200 word equivalent)

    Component 2 - 40% Technical Report (800 word equivalent)

  6. WEB DEVELOPMENT
    (Compulsory) cmu406
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    MODULE SUMMARY :

    This module will provide students with the opportunity to be proficient with tools and techniques used to create content accessed across a variety of mobile, tablet and desktop devices reliant on current client-side technologies including HTML5, CSS3, JavaScript. Students will identify the core technologies that comprise the internet and World Wide Web and their impact on the development of online content.  Students will also recognise appropriate accessibility standards and apply compliance guidelines to interactive websites.  They will review appropriate literature on website design and development to gain understandings of the planning and implementation process and identify areas for further development or study.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

      • develop an appreciation of structured web design, using appropriate tools and techniques, and present online content that is accessible across a variety of platforms and devices

      • the ability to apply and interpret standards and accessibility best practice in website design

      • develop the ability to investigate and evaluate alternative web site designs and architectures

      • explore technologies underpinning the Internet and world-wide-web.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • identify and review the core technologies that comprise the Internet and World Wide Web and their impact on the development of online content

    • apply appropriate accessibility standards

    • understand and interpret the tools, processes and techniques used to plan, design and deploy web sites

    • design and deliver online content that is accessible across a variety of devices and platforms and reflects relevant industrial standards and principles

    • engage confidently in academic and professional communication and report their actions clearly and competently

    • review and evaluate the literature on website design and development and opportunities for innovation in the delivery of online information systems.

    METHOD OF ASSESSMENT :

    Component 1 - 60% Project (1200 word equivalent)

    Component 2 - 40% Technical Report (1200 word equivalent)

Optional choices:

CMU506 – Robotics OR CMU507 – Creative Computing

  1. WORK RELATED LEARNING
    (Compulsory) cmu501
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    MODULE SUMMARY :

    This module provides the opportunity to mesh theoretical and practical learning activities. Students will be required as a key part of the module and its assessments to undertake a work placement in a computer science or computer science related setting for one hundred hours. Students will participate in a work-based learning experience, such as data collection, data analytics, mobile app development, or cybersecurity. The activity must contain elements of research, including a systematic review of the literature, critical analysis, ethical considerations and dissemination.  The module also contains an element of reflection of digital skills for the workplace, reflecting on professional development, working with others and work-based learning.  

    CONTACT HOURS :

    Scheduled   : 30.00 Independent   : 70.00 Placement   : 100.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • encourage students to take responsibility for initiating, directing and managing a work-based learning activity

    • encourage students to apply appropriate research methods and to reflect critically on their experiences

    • enable students to work collaboratively in a computer science or computer science related setting

    • generate confidence in students’ employability

    • encourage students to produce a reflective digital artefact aimed at an external audience, to contribute towards work and study transitions.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • develop a critical understanding of, and apply, research methods that are appropriate to computer science contexts

    • interpret and critically analyse collected data

    • make a clear and productive contribution to the organization through the development of recommendations arising from the work-based learning activity

    • present a creatively and critically engaging argument within an appropriate virtual environment

    • critically reflect on working as part of a team and negotiating with an organisation in meeting the needs of the computing setting they are operating within

    • define, discuss and evaluate ethical issues related to the subject adhering to the standards of Newman University Ethics Policy.

    METHOD OF ASSESSMENT :

    Component 1 - 40% Work Related Project Report (1200 word equivalent)

    Component 2 - 60% Work Placement Reflection - Digital Artefact (1800 word equivalent)

  2. CYBERSECURITY
    (Compulsory) cmu502
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    MODULE SUMMARY :

    The popularity of the Internet, coupled with the explosive growth of mobile computing devices (such as smartphones, personal digital assistants (PDAs) and laptops), has led to the world of universal electronic connectivity. In this connected world, people access data and services on the Internet and communicate with each other anywhere and anytime. While this level of connectivity may bring us many benefits such as improving our quality of life and running services with global presence but with reduced costs, it does open vast opportunities for unauthorised access to data, services and other resources and for fraud and forgeries in commercial and business activities. Therefore, it is of paramount importance to increase both awareness and knowledge in protecting data and resources from unauthorised disclosure, in guaranteeing the authenticity of data in transit, and in protecting networked systems against attacks. 

    The first part of the module covers the fundamental concepts required to understand and to work with security. These security concepts include: historical background, security and security threats, practical measures (such as identification, authentication, audit trails), security models, cryptography, network security). 

    The second part of the module provides students with the opportunity to explore computer system security via hands-on activities. Current issues relating to security will be discussed and possible solutions will be investigated.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • develop students criticality of the principles and practices of cryptography and cybersecurity

    • develop mastery of identifying and resolving security issues

    • investigate critically the cryptographic methods and security protocols and their applications for countering network-based security threats and attacks.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • articulate what is meant by computer security, what it encompasses and associated ethical considerations

    • analyse, identify and use attack tree to evaluate and classify security vulnerabilities and threats in a networked and distributed system context

    • apply appropriate cryptographic methods to achieve a given security goal, or to solve a given security problem, in a practical (efficient, usable and scalable) manner

    • describe and analyse network and internet security solutions

    • design and analyse security protocols and methods to solve specified security problems

    • engage with current research issues and directions of computer security

    • demonstrate an appreciation of the practical aspects of computer in(security), common security threats and an understanding of measures to combat them.

    METHOD OF ASSESSMENT :

    Component 1 - 25% Examination (2 hours, 750 word equivalent)

    Component 2 - 75% Workbook (2250 word equivalent)

  3. MOBILE APP DEVELOPMENT
    (Compulsory) cmu503
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    MODULE SUMMARY :

    This module aims to teach students the concepts, skills and knowledge required to develop mobile applications.  Students will appraise the tools, processes and techniques used to plan, design and deploy mobile applications.  This module provides the students with the opportunity to evaluate the technical and management dimensions of mobile applications development. The students will critically review relevant guidelines, principles and research to identify different application development strategies and build on existing software development skills to create a mobile application for a given context.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to:

     

    • develop the ability or evaluate critically the technical and management dimensions of mobile application development

    • develop the ability to appraise the tools, processes and techniques used to plan, design and deploy mobile applications

    • explain and interpret mobile application development basics - types of devices, device differences, open and proprietary coding frameworks

    • contrast different application development strategies (e.g. Web-based or Native apps)

    • debate mobile device-specific hardware features and support such as audio, video, haptic feedback, microphone, camera, location awareness etc. in the design of applications.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to:

     

    • review and apply relevant guidelines, principles and research in mobile application development

    • select and appraise appropriate tools and techniques to design, develop and deploy a mobile application

    • create and evaluate critically a mobile application for a given context

    • articulate and analyse critically the design process and functionality of the developed mobile application.

    METHOD OF ASSESSMENT :

    Component 1 - 75% Project (2250 word equivalent)

    Component 2 - 25% Individual Presentation (750 words)

  4. HUMAN COMPUTER INTERACTION
    (Compulsory) cmu504
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    MODULE SUMMARY :

    This module enables students to investigate the scope and challenges of Human Computer Interaction (HCI) and interaction design.  They will develop an understanding of HCI concepts and apply HCI methodologies to augmented reality and tangible user interfaces.  Students will investigate current user-centred design research and participate in the process of designing a high-fidelity prototype that meets user requirements. They will explain, discuss and apply the underlying principles in HCI, including human physiological, psychological and technical aspects.  Usability evaluation methods will be deployed to assess potential design options and trade-offs.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • develop an appreciation of the interdisciplinary complexities of both practical and theoretical aspects of Human Computer Interaction (HCI)

    • develop an enduring capability to participate in analysis and design work in Human Computer Interaction

    • develop an appreciation of the interaction between computer technology and people, business and society.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • articulate appropriate techniques for determining user requirements from HCI perspective

    • design and evaluate critically a high-fidelity prototype which meets user requirements

    • explain, discuss, apply and interpret the underlying principles in HCI, including psychological and technical aspects

    • participate in a user-centred design process

    • demonstrate a critical understanding of the scope and significance of HCI systems across a range of application domains.

    METHOD OF ASSESSMENT :

    Component 1 - 50% Project (1500 words equivalent)

    Component 2 - 50% Reflective VideoPaper (1500 words equivalent)

  5. MACHINE LEARNING
    (Compulsory) cmu505
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    MODULE SUMMARY :

    Machine Learning, is a subset of Artificial Intelligence, is concerned with creating learning models that allow a computer to exhibit behaviour that would normally require a human to do. Typical applications include: computer vision, speech recognition, and intelligent robots. The learning models come in various forms, such as parametric and non-parametric and probability distributions. The emphasis is on creating these models automatically from data provided and for them to act without necessarily being explicitly programmed, for example, creating a face recognition system from a data set of facial images. In the past decade, machine learning has given society effective web search, self-driving cars, practical speech recognition, and an understanding of the human genome. 

    In this module, students will learn about the most effective machine learning techniques, and gain practice in implementing them successfully. Additionally, students will learn about the theoretical underpinnings of machine learning. Topics covered include: supervised learning, unsupervised learning and best practices in machine learning. Case studies and applications will be used to illustrate best practice in machine learning.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • provide an in-depth understanding of historical and contemporary approaches to and applications of machine learning

    • introduce students to both supervised and unsupervised machine learning

    • engage students with models and algorithms for regression, classification, clustering and Markov decision processes

    • reflect critically on the professional, moral, legal and ethical issues associated with a computer science professional working within the field of machine learning.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • demonstrate their understanding of the underlying mathematical and algorithmic principles of machine learning

    • use Bayesian reasoning to construct a simple algorithm for learning in a variety of situations

    • create machine learning application using machine learning frameworks, tools and techniques to solve specified problems

    • evaluate and effectively communicate the key factors that make machine learning systems successful for various applications.

    METHOD OF ASSESSMENT :

    Component 1 - 100% Portfolio (3000 word equivalent)

  6. ROBOTICS
    (Optional) cmu506
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    MODULE SUMMARY :

    In this module, students will address the general problem of sensor-based mobile robot navigation and explore the implementation of intelligent behaviour in mobile robots. Throughout the module, students will be introduced to different characteristic problems in robotics, derive mathematical models for those problems, develop algorithms that apply these mathematical models to solve robotic problems, translate proposed algorithms into a program, and implement and test these programs on a mobile robot.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • articulate the big ideas in robotics

    • study in-depth the mathematics which underpins a robotics system

    • investigate critically the control architecture for a mobile robot system, based on sensor-based navigation and localisation algorithms

    • develop engagement with human-robot interaction

    • provide opportunities to program intelligent robot behaviour, such as computer vision, navigation, path planning and manipulation.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, will have the opportunity to: 

    • debate the big ideas in robotics

    • articulate mathematically the position and orientation of objects and compute mobile robot kinematics

    • develop a control architecture for a mobile robotic system

    • implement navigation algorithms based on sensor fusion, such as computer vision and speech recognition and environment representation using machine learning software to facilitate intelligent behaviours of a mobile robot

    • design, program and test the operation of a robotic system to perform a specific task

    • design robot environments that facilitate visual landmark-based localisation and navigation

    • reflect on the professional, moral, legal and ethical issues associated the field of robotics.

    METHOD OF ASSESSMENT :

    Component 1 - 100% Workbook (3000 word equivalent)

  7. CREATIVE COMPUTING
    (Optional) cmu507
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    MODULE SUMMARY :

    The module presents the student with the opportunity to articulate creative ideas through computing. At the end of the module, students will understand the foundational creative processes in the form of computer programs that produce audio-visual content to a high standard. The module provides the foundational aspects of programming for creativity, principles of form, structure, transformation and generative processes for image, sound and video. Students will explore the methods and conceptual tools used in the creative industries. They will also implement creative concepts that are not easily realised with commercial software packages.   A level of originality would be expected in their creative work.  Students will also understand the main concepts of signal processing, investigate how perception works, and apply their knowledge to produce innovative creations.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to:  

    • examine and review the foundational aspects of signal processing and how perception works

    • investigate critically the sources of signal and fundamental mechanism for the creation of art

    • explore the details of perception and cognitive processes and its’ importance for creative practice

    • develop the facility to program creative ideas.

    • analyse the concepts behind creative and commercial software that is in wide use.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • debate issues regarding how physical stimuli and perceived entities connect and discuss different views on how perception works

    • articulate the role of abstraction in how we perceive entities in the world

    • apply signal processing in the making of artworks

    • investigate and evaluate critically the paradoxes and philosophical problems with motion

    • generate sketches using creative technologies to produce original artwork.

     

    METHOD OF ASSESSMENT :

    Component 1 - 100% ePortfolio (3000 word equivalent)

Optional choices:
CMU601 – Project OR CMU602 Negotiated Work-based Related Project
CMU605 – Game Design and Development OR CMU606 - Communicating Technology

  1. PROJECT
    (Optional) cmu601
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    MODULE SUMMARY :

    The final project and critical evaluation will be structured to assess the knowledge and understanding by means appropriate to individual students, though all approaches will lead to the production of a significant piece of work that involves the demonstration of advanced practice in computer science. All approaches will be accompanied by a critical self- evaluation of the outcomes achieved.  Students would integrate concepts and skills learned throughout the degree course to substantial open-ended problems. The module will increase students understanding of applied, investigational or theoretical approaches to real word problems.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 364.00 Placement   : 0.00 Total   : 400.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • provide an integrative structure to enable student’s ability to identify, analyse and critically evaluate research evidence related to a selected area of computing

    • provide students with a critical awareness of appropriate and ethically sound research methods in relation to identified research or operational purposes and justify their use

    • embed a perceptive ability to work constructively with an advisory tutor, recognizing that the content and execution of the project belongs to the student

    • provide an opportunity to further enhance the ability of the student to discover, analyse, evaluate, synthesise and present a solution to a business management problem or enquiry.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • formulate clearly a research question and/or an issue of advanced practice

    • conduct a systematic literature review of a focal problem, identify current key concepts, knowledge and perceived gaps

    • execute effectively and efficiently a chosen approach to data elicitation

    • analyse and evaluate appropriately situated knowledge contained in outcomes of data elicitation

    • propose further action to implement advanced practice supported by the outcomes of the enquiry, including consideration of risk involved and approaches to its management

    • reflect upon the learning process embedded in the completion of their final project and identify a strategy for further personal development and lifelong learning.

    critically define, discuss and evaluate ethical issues related to the subject of the research to the standards of Newman University Ethics Policy

    METHOD OF ASSESSMENT :

    Component 1 - 80% Project Report (8000 words)

    Component 2 - 20% Inidividual Presentation (2000 word equivalent)

  2. NEGOTIATED WORK-BASED RESEARCH PROJECT
    (Optional) cmu602
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    MODULE SUMMARY :

    This module forms an alternative option for undertaking the 40-credit capstone final project.    It is designed to offer students ‘real life’ problem-solving skills in undertaking a work-based related project. Learners should complete a minimum of 100 hours in the workplace. The project is often employer-generated or can be negotiated with an employer in a computer science or computer related field.  The completed project should be of benefit to the organisation.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 364.00 Placement   : 0.00 Total   : 400.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • enable students to take responsibility for initiating, directing and managing a negotiated work linked research project

    • encourage students to use appropriate research methods

    • enable students to work collaboratively with an employer in a computer science or computer science related setting.

    • generate confidence and security in students’ employability on graduation

    • encourage students to produce a reflective digital artefact aimed at an external audience, to contribute towards work and study transitions

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • successfully negotiate and design a work-based related project

    • develop a critical understanding of, and apply, research methods that are appropriate to computer science contexts

    • interpret and critically analyse gathered information

    • make a clear and productive contribution to the organization through the development of recommendations arising from the work-based related project

    • present a creatively and critically engaging argument demonstrating criticality with literature related to the topic

    • critically reflect on working as part of a team and negotiating with an organisation in meeting the needs of the computing setting

    • critically define, discuss and evaluate ethical issues related to the subject of the research to the standards of Newman University Ethics Policy.

    METHOD OF ASSESSMENT :

    Component 1 - 80% Project Report (8000 words)

    Component 2 - 20% Individual Presentation (2000 word equivalent)

  3. DEEP LEARNING
    (Compulsory) cmu603
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    MODULE SUMMARY :

    Deep Learning has shown its success in many areas including computer vision, speech and audio processing, natural language processing, robotics, bioinformatics and chemistry, video games, search engines, online advertising and finance. Deep Learning is a particular kind of Machine Learning technique that allows computer systems to improve with experience and data, and achieves great power and flexibility by learning to represent the world as a nested hierarchy of concepts. In recent years, deep learning has seen tremendous growth in its popularity and usefulness, due in large part to more powerful computers, larger datasets and techniques to train deeper neural networks.

     

    This module introduces a wide range of deep learning and other state of art techniques in Artificial Intelligence for solving real-world problems. Basic concepts on statistics and applied maths that thread through key elements in Machine Learning techniques will be discussed throughout the module. Students will study how to build suitable Artificial Intelligence systems that can operate in complicated, real-world environments. The module also prepares students to explore further challenges and opportunities to improve deep learning and Artificial Intelligence and bring them to new frontiers.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • articulate the state of the art in the field of Artificial Intelligence in the context of Deep Learning

    • construct intelligence systems for various practical applications

    • evaluate the fundamentals of modern multi-layered neural networks

    • contrast the algorithms used to train model architecture

    • evaluate frameworks and implement core algorithms to reinforce theory and principles of Deep Learning.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • apply mathematical methods for processing and interpreting the data within deep learning applications

    • develop deep learning applications, using core deep algorithms, such as backpropagation

    • evaluate existing methods applicable for deep learning within the context of current trends

    • engage with the fundamental principles, theory and approaches for learning with deep neural networks

    • critique the key concepts, issues and practices when training and modelling with deep learning architectures

    • reflect on the professional, moral, legal and ethical issues associated with a computer science professional working within the field of deep learning.

    METHOD OF ASSESSMENT :

    Component 1 - 60% Portfolio (2400 word equivalent)

    Component 2 - 40% Project (1600 word equivalent)

  4. INTERNET OF THINGS
    (Compulsory) cmu604
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    MODULE SUMMARY :

    Low-cost network devices add eyes, ears or sensors and arms, legs or actuators to the Internet. These devices are then connected to a computer, either physically, via wireless or through the cloud, communicating live data. This computer will then utilise machine or deep learning in the cloud. This field of study is referred to as the Internet of Things (IoT). 

    This module will cover the context and the history of the IoT, the hardware, communications protocols and security systems it relies on, and the cloud-side analytics that makes sense of the data produced. It will provide practical hands-on experience of common IoT devices (sensors, actuators, microcontrollers), and examine a range of commercial platforms. 

    Students will be provided with a wifi microcomputer and will program live IoT applications using that device. Students will have the opportunity to produce their own IoT device with a range of hardware and capabilities. Emphasis is placed on the versatility of components that can be integrated into such systems, as well as the diversity of data types produced by IoT edge nodes. Development of IoT applications also requires communication between different level (layers) of IoT architecture with the associated security and privacy issues.

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • demystify the IoT paradigm

    • offer insight into the IoT components and explain the different principles and the several aspects of designing IoT architectures

    • focus on the Edge of the IoT that is the “Things” (i.e. the edge devices)

    • analyse several IoT areas of application, such as smart grids, home automation, and industrial IoT to demonstrate the different requirements and constraints in designing practical IoT architectures for these segments

    • analyse critically the importance of the security, trust and privacy issues for IoT and present techniques and tools to address these

    • deliver practical experience of programming IoT devices, capturing their data and developing visual analytics of that data.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • explore the structure and components that underpin IoT systems

    • evaluate critically the IoT architectures and related design principles and requirements

    • investigate applications and communication protocols for the devices on the Edge

    • create and interrogate an IoT system for a specific application based on a holistic overview.

    METHOD OF ASSESSMENT :

    Component 1 - 60% Project (2400 word equivalent)

    Component 2 - 40% Portfolio (1600 word equivalent)

  5. GAME DESIGN AND DEVELOPMENT
    (Optional) cmu605
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    MODULE SUMMARY :

    This module aims to teach students the concepts, skills and knowledge required to develop, design and prototype games. This module provides an introduction to games design and the games industry and outlines the key elements of game development. The module will provide contextual knowledge of the games industry (past and present; the UK and international), different genres, technology and tools, and roles, good practice, and current challenges of games design and development. The wider influence of games within contemporary culture and education will also be considered, specifically the application of ludic design principles in other creative sectors (e.g. ‘gamification’).

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • provide students with an in depth understanding of the fundamental concepts of game design and the development process

    • develop the students’ ability to use and interpret multimedia content effectively and independently in the design of games

    • enhance the students’ scripting skills and introduce them to industry standard scripting and game content authoring tools.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • articulate the key principles and approaches underpinning game design and development

    • integrate multimedia content effectively in a computer games context

    • create hi-fidelity prototype computer games of a non-trivial nature using industry standard, multimedia authoring tools and scripting technologies.

    METHOD OF ASSESSMENT :

    Component 1 - 70% Project (2800 word equivalent)

    Component 2 - 30% Technical Report (1200 word equivalent)

  6. COMMUNICATING TECHNOLOGY
    (Optional) cmu606
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    MODULE SUMMARY :

    In this module, students have the opportunity to learn and reflect upon how computer science is taught in schools both as a passive observer and an active participant. Students will act as ambassadors for the subject by sharing their knowledge of and passion for computer science, motivate learners and hopefully inspire them to understand an aspect of the beauty and joy of computer science. Working alongside an in-service computing teacher, students will have the opportunity to communicate computer science concept(s) to learner(s) and reflect upon this experience. This experience will enable students to develop transferable employability skills; such as organising and planning, communication, and working within a professional team; within a professional environment. 

    For those students who wish to pursue a career as a computing teacher teaching computer science, then this module provides a vehicle for gaining valuable insight into not only how computer science is taught in schools but also the role and responsibilities of a computing teacher. 

    In order to take this module, students will be required to attend orientation training regarding working with learners and conducting themselves within a school-based setting. This orientation will be held in the first semester of the final year of this programme. 

    This module has designed in accordance with the recommendations and guidance of the national Undergraduate Ambassador Scheme (UAS).

    CONTACT HOURS :

    Scheduled   : 24.00 Independent   : 106.00 Placement   : 70.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • provide students with the opportunity to teach computer science learning episodes in a school-based environment

    • deepen students’ insight into a specific aspect of computing education within a school context

    • allow students to communicate computer science concepts to either an individual learner or group of learners using computer science learning episodes

    • enable students to work with a computing teacher to plan for and teach an aspect of computer science

    • enable students to support learners deliver their knowledge, skills and understanding of an aspect of computer science

    • enable students to critique their engagement in planning, delivering and supporting computer science learning activities.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • articulate an appreciation of the needs of individual learners in either a computing lesson or an extra-curricular computing session

    • plan for the delivery of a series of computing learning episodes

    • create resources to support the teaching of a computer science topic

    • self-reflect upon the learning episodes delivered using an appropriate framework

    • critically reflect on how a specific area of computer science education is taught within a school context.

    METHOD OF ASSESSMENT :

    Component 1 - 60% Self-Reflective Journal (2400 word equivalent)

    Component 2 - 40% Poster Presentation (1000 word equivalent)

  7. CLOUD APPLICATION DEVELOPMENT
    (Compulsory) cmu607
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    MODULE SUMMARY :

    This module aims to introduce students to the paradigm of cloud computing, where technology-related functions are provided as a service to users in order to perform resource-intensive tasks such as data analysis and machine learning. They will learn formal methods and techniques for designing and implementing advanced cloud-based applications. Students will have an appreciation for Artificial Intelligence and Semantic Web research related to cloud computing. They will investigate big data computing using cloud-based technologies and apply the skills and knowledge gained to design, develop and deploy an interactive data-drivencloud-based application to solve programming problems.  

    CONTACT HOURS :

    Scheduled   : 36.00 Independent   : 164.00 Placement   : 0.00 Total   : 200.00

    MODULE CURRICULUM LED OUTCOMES :

    This module aims to: 

    • examine cloud computing at the infrastructure, platform and service level

    • provide an opportunity for constructing cloud-based applications for specific purposes e.g. data mining, machine learning

    • investigate the architectural components of a cloud-based solution e.g. web servers, application servers, database servers and client machines

    • research the legal, ethical and social issues associated with cloud computing.

    LEARNING OPPORTUNITIES :

    Students will, by the end of the module, have the opportunity to: 

    • critically examine key concepts and issues in cloud-based computing

    • critique appropriate theories, techniques and tools for information modelling, management and security in cloud computing

    • apply problem-solving strategies in the context of creating a cloud computing solution.

    METHOD OF ASSESSMENT :

    Component 1 - 70% Project (2400 word equivalent)

    Component 2 - 30% Report (1600 word equivalent)