Pearson BTEC Level 5 Higher National Diploma in Computing
Summary
The HND in Computing is a work-related qualification for those taking their first steps into employment, or for those already in employment and seeking career development opportunities. The School of Computing has established close links with both local business and the local community. Wherever practicable, assessment on the program reinforces these links.
The course provides a blend of a year-long units. The units are sequenced to provide you with a coherent learning experience. The HND program has a total value of 240 credits and is equivalent to approximately 2,400 hours total learning time.
Throughout the program emphasis will be placed upon reflection, analysis, environmental impact, critical thinking and personal development.
Assessment
The teaching strategy is designed to supplement your existing knowledge and to encourage your acquisition of new subject knowledge while supporting you in the move towards a greater degree of independence and self-direction.
Assessments may include elements of: practical assessments; portfolios of evidence; ‘in-class’ tests; lab work; case studies; examinations, both open and closed book; reflective activities where you look back over your experiences, analyse them with the assistance of relevant theory and reflective tools, and learn from the experience; online discussions that you have had with your peers, tutors and invited contributors to the program; oral and written reports; journals, blogs and log books; plans (e.g. action plans, plans for your group activities); presentations; time-constrained tasks.
Qualification Requirements
Minimum of three IGCSE at Grade D/4-5 or above and including Mathematics and English. English Proficiency Test. If you do not meet the criteria for Mathematics and English you will be invited for an interview where you will be required to sit a numeracy and literacy skills assessment.
Fees
Tuition Fees AED 38,000
Registration Fee AED 2,000
UNIT CONTENT
UNIT 1: Programming
Learning Outcome 1
Define basic algorithms to carry out an operation and outline the process of programming an application.
Learning Outcome 2
Explain the characteristics of procedural, object-orientated and event-driven programming, conduct an analysis of a suitable Integrated Development Environment (IDE).
Learning Outcome 3
Implement basic algorithms in code using an IDE.
Learning Outcome 4
Determine the debugging process and explain the importance of a coding standard.
UNIT 2: Networking
Learning Outcome 1
Examine networking principles and their protocols.
Learning Outcome 2
Explain networking devices and operations.
Learning Outcome 3
Design efficient networked systems.
Learning Outcome 4
Implement and diagnose networked systems.
UNIT 3: Professional Practice
Learning Outcome 1
Demonstrate a range of interpersonal and transferable communication skills to a target audience.
Learning Outcome 2
Apply critical reasoning and thinking to a range of problem-solving scenarios.
Learning Outcome 3
Discuss the importance and dynamics of working within a team and the impact of team working in different environments.
Learning Outcome 4
Examine the need for Continuing Professional Development (CPD) and its role within the workplace and for higher level learning.
UNIT 4: Database Design and Development
Learning Outcome 1
Use an appropriate design tool to design a relational database system for a substantial problem.
Learning Outcome 2
Develop a fully functional relational database system, based on an existing system design.
Learning Outcome 3
Test the system against user and system requirements.
Learning Outcome 4
Produce technical and user documentation.
UNIT 5: Security
Learning Outcome 1
Assess risks to IT security.
Learning Outcome 2
Describe IT security solutions.
Learning Outcome 3
Review mechanisms to control organisational IT security.
Learning Outcome 4
Manage organisational security.
UNIT 6: Managing a Successful Computing Project
Learning Outcome 1:
Establish project aims, objectives and time frames based on the chosen theme.
Learning Outcome 2:
Conduct small-scale research, information gathering and data collection to generate knowledge to support the project.
Learning Outcome 3:
Present the project and communicate appropriate recommendations based on meaningful conclusions drawn from the evidence findings and/or analysis.
Learning Outcome 4:
Reflect on the value gained from conducting the project and its usefulness to support sustainable organisational performance.
UNIT 11: Maths for Computing
Learning Outcome 1
Use applied number theory in practical computing scenarios.
Learning Outcome 2
Analyse events using probability theory and probability distributions.
Learning Outcome 3
Determine solutions of graphical examples using geometry and vector methods.
Learning Outcome 4
Evaluate problems concerning differential and integral calculus.
UNIT 12: Data Analytics
Learning Outcome 1
Discuss the theoretical foundation of data analytics that determine decision-making
processes in management or business environments.
Learning Outcome 2
Apply a range of descriptive analytic techniques to convert data into
actionable insight using a range of statistical techniques.
Learning Outcome 3
Investigate a range of predictive analytic techniques to discover new
knowledge for forecasting future events.
Learning Outcome 4
Demonstrate prescriptive analytic methods for finding the best course of
action for a situation.
UNIT 13: Computing Research Project
Learning Outcome 1
Examine appropriate research methodologies and approaches as part of the research process.
Learning Outcome 2
Conduct and analyse research relevant to a computing research project.
Learning Outcome 3
Communicate the outcomes of a research project to identified stakeholders.
Learning Outcome 4
Reflect on the application of research methodologies and concepts.
UNIT 14: Business Intelligence
Learning Outcome 1
Discuss business processes and the mechanisms used to support business decision-making.
Learning Outcome 2
Compare the tools and technologies associated with business intelligence functionality.
Learning Outcome 3
Demonstrate the use of business intelligence tools and technologies.
Learning Outcome 4
Discuss the impact of business intelligence tools and technologies for effective decision-making purposes and the legal/regulatory context in which they are used.
Unit 16: Cloud Computing
Learning Outcome 1
Demonstrate an understanding of the fundamentals of Cloud Computing and
its architectures.
Learning Outcome 2
Evaluate the deployment models, service models and technological drivers of
Cloud Computing and validate their use.
Learning Outcome 3
Develop Cloud Computing solutions using service provider’s frameworks and
open source tools.
Learning Outcome 4
Analyse the technical challenges for cloud applications and assess their risks.
Unit 18: Discrete Maths
Learning Outcome 1
Examine set theory and functions applicable to software engineering.
Learning Outcome 2
Analyse mathematical structures of objects using graph theory.
Learning Outcome 3
Investigate solutions to problem situations using the application of Boolean
algebra.
Learning Outcome 4
Explore applicable concepts within abstract algebra.
Unit 21: Data Mining
Learning Outcome 1
Discuss the historical and theoretical foundation of data mining, its scope,
techniques, and processes.
Learning Outcome 2
Investigate a range of data mining techniques to discover patterns and
relationships in large data sets.
Learning Outcome 3
Illustrate how a data mining algorithm performs text mining to identify
relationships within text.
Learning Outcome 4
Evaluate a range of graph data mining techniques that recognize patterns
and relationships in graph-based technologies.
Unit 24: Forensics
Learning Outcome 1
Examine the processes and procedures for carrying out digital Forensic
Investigation.
Learning Outcome 2
Discuss the legal and professional guidelines and procedures for carrying out
digital Forensic Investigation.
Learning Outcome 3
Use a tool or tools to conduct digital Forensic Investigation on devices or
networks or cyber attacks.
Learning Outcome 4
Develop a Test Plan and make some recommendations for use in digital
Forensic Investigation.
Unit 27: Artificial Intelligence
Learning Outcome 1
Analyse the theoretical foundation of artificial intelligence, current trends
and issues to determine the effectiveness of AI technology.
Learning Outcome 2
Implement an intelligent system using a technique of the top-down
approach of AI.
Learning Outcome 3
Implement an intelligent system using a technique of the bottom-up
approach of AI.
Learning Outcome 4
Investigate and discuss a range of emerging AI technologies to determine
future changes in industry.