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Introduction
Why choose this course?
Key features
Gain an industry-recognised qualification and a skill set sought by employers across the industry.
Learn from our computing experience built over more than 50 years, a long-standing history allowing you to draw on a wealth of research and academic expertise.
Our computer science and engineering and technology subjects have scored highly in the Times Higher Education’s 2020 World University Rankings, meaning you can benefit from the outstanding level of research, teaching and learning on offer at DMU.
Enhance your employability and gain industry experience by undertaking an optional work placement. Previous students have benefited from placements at leading organisations including at Hewlett-Packard, Intel Corporation, Thomson Reuters, E.ON, GlaxoSmithKline, TNT Express, and AstraZeneca.
Develop your practical skills in our specialist facilities, with 100 computer workstations on campus divided into five interconnected laboratories, each with 20 high-specification PCs running Windows/Linux.
Benefit from Education 2030, where a simplified ‘block learning’ timetable means you will study one subject at a time and have more time to engage with your learning, receive faster feedback and enjoy a better study-life balance.
Overview
Please note: this course was previously titled 'Computing for Business BSc (Hons)'
The field of data analytics is becoming increasingly more relevant and important. Insight-driven businesses are said to be growing at an average of more than 30 per cent each year, creating a demand for professionals skilled in data analytics.
This course provides a broad understanding of information systems coupled with in-depth exploration of analytics knowledge and concepts to help you derive valuable information and insights from data. The course covers a range of subjects to prepare for a career in the sector, and benefits from insight from DMU’s internationally-renowned research institutes, embedding ethics and the impact of computing and technology within the modules.
Professionalism within an industry context is emphasized throughout, with strong links to BCS, The Chartered Institute for IT. Students are exposed to industry-standard concepts, tools and technologies, exploring the fundamental underlying principles of data analytics. Our teaching staff contribute to the field through internationally-recognised research or industrial consultancy, and many are members of centres that pioneer cutting-edge research.
On graduating from this course, our students are equipped with the skills needed for successful careers in industry or academia, as competent and independent lifelong learners. The programme will prepare you for careers in fields such as data and systems analysis and design, system, security, project and knowledge management, big data architect roles, data consultant roles and business consultancy.
Modules
Entry Criteria
ENTRY REQUIRED DOCUMENTS
Home Office Share Code
For EU students only.
IF no Qualification
Please provide CV with at least 2 years of work experience, and employee reference letter.
Five GCSEs at grade C or above, including English and Mathematics or equivalent, plus one of the following:
Normally 112 UCAS points from at least two A-levels or equivalent or
BTEC National Diploma/ Extended Diploma at DMM or
Pass in the QAA accredited Access to HE. English and Mathematics GCSE required as a separate qualification as equivalency is not accepted within the Access qualification. We will normally require students to have had a break from full-time education before undertaking the Access course or
International Baccalaureate: 26+ points or
T Levels Merit
Portfolio Required: No
Interview Required: No
We welcome applications from mature students with non-standard qualifications and recognise all other equivalent and international qualifications.
Contextual offer
To make sure you get fair and equal access to higher education, when looking at your application, we consider more than just your grades. So if you are eligible, you may receive a contextual offer. Find our more about contextual offers.
English language
If English is not your first language then an IELTS score of 6.0 overall with a minimum of 5.5 in each component (or equivalent) is essential.
English Language tuition, delivered by our British Council accredited Centre for English Language Learning, is available both before and throughout the course if you need it.
Year 1
Block 1: Foundations of Computing
This module introduces students to the professional context of computer science, software engineering, cyber security, and digital forensics. It introduces mathematical structures that provide a basis for computer science and cyber security to prepare students with the necessary skills in this domain. Students gain skills to learn the concepts of computer science cyber security.
In this module the students will learn the mathematical foundation of computing such as Logic and Boolean Algebra, Set Theory, Probability and Statistics, Relations, Functions, and Modular Arithmetic. The evolution of computational IT infrastructures (e.g., general-purpose mainframe and minicomputer computing, personal computers, client/server networks, enterprise computing, cloud, and mobile computing.) will also be presented and discussed from hardware, software, OSs, applications, data management and storage internet platforms.
Lecture: 24 hours
Seminar: 48 hours
Self-directed study: 156 hours
Consolidation: 40 hours
Revision: 30 hours
Assessment: 2 hours
Total 300 hours
Block 2: Programming in Python
The Python programming module has no pre-requisites; it is designed for learners with no prior programming experience and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. As well as covering the basics of how one constructs a program from a series of simple instructions in Python, this module aims to teach students the basics of programming computers using Python.
Students will be introduced to fundamental theories and related concepts of the Python programming language; the module will help the learner develop a sufficiently rich and detailed, generally applicable background and hands-on practical knowledge. Learners will solve problems, explore real-world software development challenges, and create practical applications.
Workshop/Lectures: 40 hours
Practical/Large Group: 72 hours
Self-directed study: 136 hours
Assessment: 52 hours
Block 3: Data Analytics and Statistics
Introduces the skills on data analytics and basic quantitative techniques for data collection, summary and presentation. Students will develop an understanding of basic concepts associated with the analysis and interpretation of statistical data within a business and organizational context.
This module will allow students to understand and present financial data within a business and organisational structure. Students will be able to apply financial mathematical techniques to simple but real life scenarios to make decisions. The module will also introduce the formulation, solution and interpretation of linear programming models and cover network models and project management.
Lecture: 24 hours
Seminar: 24 hours
Practical: 24 hours
Self-directed study: 180 hours
Assessment: 48 hours
Block 4: Information Systems Analysis and Design
This module gives an insight into the many tasks that must be carried out during the analysis and design stages of an information system development project. It provides a practical introduction to the techniques used at different stages of a project. It also illustrates how these tasks fit together within the overall project framework, and how they can be managed to ensure that the aims of the project are met.
Lecture: 24 hours
Seminar: 24 hours
Practical: 24 hours
Self-directed study: 104 hours
Assessment: 60 hours
Year 2
Block 1: Advanced Data Analytics and Visualisation
This module builds on the introduction to the Python programming language and data analytics modules that are studied at Level 4. In this module further data analytics using Python is taught, covering a wide range of analytics including text analytics, predictive analytics and sentiment analysis. The module will also include the use of Python for data extraction, storage and analysing textual and numeric data. Visualisation is also covered alongside data analytics in this module.
Lecture: 5 hours
Seminar: 6 hours
Practical: 35 hours
Workshop: 18 hours
Self-directed study: 86 hours
Consolidation: 60 hours
Reading: 40 hours
Assessment: 50 hours
Block 2: Operational Research
This module aims to introduce a range of techniques, that typically fall under the headings of Operational Research, Management Science or Decision Science, which can be used as part of an effective and pragmatic decision-making process. The techniques covered include a selection of the more popular and commonly applied methodologies which have wide ranging applications such as optimisation methods, and forecasting, amongst others. The emphasis throughout is on the formulation (structuring) of real problems and the development of practical solution using computer software.
Lecture: 22 hours
Seminar: 22 hours
Practical: 22 hours
Self-directed study: 190 hours
Assessment: 44 hours
Block 3: Introduction to Information Security
The module will investigate the importance of Information Security in the context of Information Systems. The module will be investigating the challenges to application and system developers in relation to the requirement for secure design and implementation. The module is a foundation of security foundations as required in terms of requirements analysis and the design of software. The module will be providing a theoretical framework in providing security solutions with reference to secure application development.
Lecture: 15 hours
Seminar: 30 hours
Self-directed study: 55 hours
Assessment: 50 hours
Block 3: Information and Database Development
In an emerging digital world, data is essential to all aspects of human life. What is of more importance, is how data is efficiently stored, retrieved, and presented in a way that makes sense. using appropriate database management systems (DBMS). This module will take students through the fundamentals of DBMS, shedding light onto the two broad categories of DBMS: relational (structured) and non-relational (unstructured) databases. Students will understand the business and technical motivations behind the use of specific DBMS for managing information in specific situations.
Practical: 10 hours
Lecture: 20 hours
Tutorial: 10 hours
Reading: 20 hours
Collaborative: 10 hours
Reflection: 20 hours
Revision: 20 hours
Assessment: 40 hours
Block 4: Integrated Project
The module will take the form of a taught project module allowing students to draw up the specification, documentation and early prototype for a constrained system. Student will be encouraged to work in teams providing opportunity to experience modern techniques such as Agile/Scrum development. Although no specific language is explicitly named for the module it would be wise to select a family of languages / development environments that allow student to demonstrate a range of modern technical skills.
Practical: 48 hours
Lecture: 24 hours
Collaborative: 40 hours
Revision: 40 hours
Consolidation: 148 hours
Year 3
Block 1: Advanced Statistics for Business
This module emphasis on simple and multiple linear regression and regression analysis. It also emphasis on decision analysis, time series analysis and forecasting, optimization and the information to be found by the categorization of data into discrete groupings with similar properties. Integrating the underlying theory with a thorough practical grounding using modern laboratory software, students will be taught to formulate and model the problems mathematically. They will learn to apply standard software packages, such as Excel LP Solver, Minitab, SAS etc. Students will be trained in presenting, interpreting and critically analyzing the result of the problems.
Learning, teaching and assessment activity hours for the module:
Lecture: 11 hours
Seminar: 11 hours
Practical: 11 hours
Self-directed study: 57 hours
Assessment: 60 hours
Block 2: Advanced Business Modelling
This module provides an overview of data analytics practices and their implications in businesses. Analysing business cases and running hands on-experiments on data, we explore how organisations leverage new data resources to develop and implement emerging business ideas, innovating the process of value creation and transforming their relationships with their customers and other stakeholders. The module delves into business practices, structures and processes that leverage big data generated in organisations to create value.
Lecture: 12 hours
Practical (Q&A): 12 hours
Self-directed study: 106 hours
Assessment: 20 hours
Block 3: Business Systems Solutions
The aim of this module is to provide students with the essential knowledge to critically evaluate IT decisions that are made at managerial level. Students will explore the implications of digital transformation, and the changing roles of the C-Suite to accommodate global changes in the business environment. The role of IT and different solutions available to a business, based on their need will be discussed; for example, enterprise systems, cloud-based systems, and business intelligence/analytics solutions.
With the growing role of data and emerging technology, students will also explore the importance of strategic, tactical and operational decision-making and the role of business analytics in supporting the business problem solving process. Finally, students will also explore and understand the ethical implications of IT, which influence the decisions around how IT is designed, implemented and used in an organisation.
Block 4: Final Year Project
The Final Year Project enables students to undertake an individual project on an approved topic of interest, that addresses significant Computing and Information Systems related problems relevant to the Programme of study. The Project provides an opportunity for the students to integrate many of the threads of their Programme of study and to extend their work beyond the taught elements through with research and self-learning.
Lecture: 8 hours
Online interactive workshop: 8 hours
Supervisor meetings: 5 hours
Self-study: 219 hours
Assessment: 60 hours
Optional modules (select one)
Privacy and Data Protection
There continues to be a growth of databases holding personal and other sensitive information in multiple formats including text, pictures and sound. The scale of data collected, its type and the scale and speed of data exchange have all changed with the advent of ICT. Whilst the potential to breach privacy continues to increase organisations are subjected to a considerable amount of legislation governing privacy and data protection.
This module examines the balance between maintaining business effectiveness, legal compliance and professional practice in the field of IT/IS.
The module will address the legal, social and technological aspects of privacy and data protection, consider privacy enabling technologies and privacy invasive technologies and identify and evaluate the role of the computer professional in providing privacy and data protection.
Lecture: 40 hours
Seminar: 90 hours
Self-directed study: 90 hours
Assessment: 80 hours
Advanced Database Management and Programming
Based on modules studied in previous years involving databases and computer programming, this module provides the student with further training on the essentials of advanced database management and programming, developing the student's ability to differentiate between relational databases and non-relational databases.
It develops the skills to choose a suitable database for an application from a business perspective to meet stated requirements using realistic scenarios and the ability to analyse semi-structured data and to choose an appropriate storage structure. It also develops skills in database design and data retrieval using a variety of complex data structures and NoSQL programming including aggregation methods.
Practical: 20 hours
Lecture: 40 hours
Online learning: 60 hours
Reading: 60 hours
Reflection: 60 hours
Revision: 60 hours
Data Mining
Data mining is fast becoming essential to the modern competitive business world. This module aims to review the methods available for uncovering important information from large data sets; to discuss the techniques and when and how to use them effectively.
The module uses the data mining tool SAS Enterprise Miner. SAS is a comprehensive data management software package that combines data entry and manipulation capabilities with report production, graphical display and statistical modelling.
Lecture: 20 hours
Practical: 40 hours
Self-directed study: 200 hours
Assessment: 40 hours
Information and Communication Technologies for Development
This module will expose students to issues that influence the adoption, implementation, uptake, and sustainability of ICTs (Information and Communication Technologies) in developing countries. Students will recognise the historical perspectives to the ICT4D concept and why it offers significant possibilities towards addressing some diverse development issues, but also at times exacerbating these existing issues.
Students will learn how to apply theoretical frameworks, such as (but not limited to), the ICT4D value chain, stakeholder matrix, and responsible research and innovation (RRI), in the analysis of ICTs issues and appraisal of ICT implementation solutions and uptake status of a developing country. In addition, the module will discuss the United Nations (UN) Sustainable Development Goals (SDGs) and debate how ICTs might, if at all, progress these Goals.
Lectures: 50 hours
Seminars: 30 hours
Reading: 40 hours
Collaborative: 20 hours
Reflection: 40 hours
Revision: 40 hours
Assessment: 80 hours
Note: All modules are subject to change in order to keep content current.
Assessment
ASSESSMENT METHODS
1. INTERNAL ENGLISH TEST if you don't have an English accredited certificate
2. Academic Interview
Teaching and assessments
The compulsory modules on this course ensure that students learn by a combination of practical experience, self-study and research. The option modules allow students the opportunity to specialise.
The modules making up the course employ a range of learning and teaching strategies including: (1) staff directed teaching and learning via lectures, seminars, laboratories; (2) case-study and lab based exercises for the dissemination of knowledge, information and the demonstration of processes and techniques; (3) student centred learning via collaborative and group based learning by group assignments and projects, (4) individual independent learning using literature sources, internet sources and further research (incl. Web based resources) (5) presentation of findings, report writing, assignments, practice (6) practical work based exercises for the development of skills and understanding and (7) project-based learning to develop research, presentation and communication skills.
Assessment methods and assessment criteria are vested in the individual modules constituting the programme. Each module template specifies the assessment methods and reassessment details which are appropriate to the aims and objectives and the teaching and learning strategy of the module. Normally some modules are assessed by a combination of coursework and a phase test. Where subject content of the module is more appropriate to be assessed using coursework, these modules are assessed by 100% coursework. Methods of assessment for the modules therefore may include: Time constrained phase tests, Portfolios of work, Laboratory exercises, Oral examinations, Demonstrations, Individual & individually assessed group work, Project work, Reports & presentations and Research reports. When needed all work is submitted to Turnitin.
Career Opportunities
Graduate Careers
Sainsbury's partnership kick-starts careers for 16 DMU students.
Sixteen De Montfort University Leicester (DMU) students have secured sought-after jobs with Sainsbury’s before graduating this summer, thanks to a fruitful partnership.
DMU has been working closely with the supermarket giant to raise awareness of the software engineer positions available at the company’s store support centre in Coventry.
Inviting Sainsbury’s to a networking event last June resulted in three DMU graduates being hired. This year representatives from the company - including those graduates - addressed more than 200 students in the School of Computer Science and Informatics.
"Computing has given me fundamental knowledge in different areas. The course has taught me programming skills that are attractive to employers, such as visual web development, HTML5, C# programming, database management and reporting." Egle Sciglinskaite, Computing BSc (Hons)
DMU Global
Our innovative international experience programme DMU Global aims to enrich studies, broaden cultural horizons and develop key skills valued by employers.
Through DMU Global, we offer an exciting mix of overseas, on-campus and online international experiences, including the opportunity to study or work abroad for up to a year.
Previous DMU Global trips have seen Computing and Computer Science students explore the Silicon Docks in Dublin and be inspired by the educational and networking opportunities at the SAS Global Forum in Dallas.
Placements
Placements can enhance your career prospects and give you the chance to use theory from the classroom in a real-world scenario before you have graduated.
Our Computing for Business students have recently secured placements at companies such as GE Aviation, Next Plc, Automotive Insights Ltd, Go Inspire and Onvu Retail Ltd.
Valuable placement year kick-starts Karishma's career.
Graduating with a First and embarking on her dream career during a global pandemic is thanks to completing a placement year, according to Karishma Samani.
The Computing for Business graduate, who joined De Montfort University Leicester (DMU) through Clearing four years ago, secured a job in February with Kainos, an award-winning company specialising in digital solutions for commercial, public and healthcare clients worldwide.
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