Computing Technologies

Admission Requirements

• Typical Age: 21+
• Prior Qualifications: Completion of Level 6 studies, such as a Bachelor’s degree in Computing, Information Technology, or a related field.
• Professional Experience: In certain cases, applicants with at least 5 years’ management experience may be considered.
• International Qualifications: Equivalent qualifications may include:
  • A Bachelor’s degree in a relevant discipline or extensive work experience in IT
• English Proficiency (for non-native speakers): IELTS 6.0, CEFR level B2, or equivalent.
• Additional Guidance: For assistance with qualification equivalency or language requirements, please contact our admissions office.

Structure of the Qualification

• Total Credits: 120 ECTS
• Modules: 5 mandatory units and two optional units allow learners to specialise according to career interests.

Core Modules

1. Managing Innovation and Change in Computing (20 Credits): Focuses on strategies for fostering innovation and managing technological changes within organizations.
2. Systems Development and User Experience (UX) (20 Credits): Teaches design methodologies that prioritize user experience, covering usability, prototyping, and iterative testing.
3. Implementing and Managing Cyber Security (20 Credits): Provides essential knowledge for managing organizational cyber security, including threat analysis and protection strategies.
4. Business Intelligence Systems (20 Credits): Examines data-driven decision-making, including data modeling, dashboard creation, and analytics.
5. Independent Project (20 Credits): A practical project where learners apply computing skills to a chosen area, demonstrating problem-solving and project management capabilities.

Optional Units

Select two out of the following elective courses:

1. Agile Transformation (10 Credits): Introduces Agile methodologies for rapid project delivery, emphasising flexibility, team collaboration, and continuous improvement.
2. Enterprise Resource Planning (ERP) Systems (10 Credits): Focuses on implementing and managing ERP systems to optimize organizational efficiency and resource management.
3. Mobile Application Development (10 Credits): Covers the fundamentals of mobile app development, including UI/UX design, cross-platform development, and deployment.
4. Data Analytics and Big Data (10 Credits): Explores data processing techniques and big data tools to analyze large datasets, identify trends, and support decision-making.
5. Networking and Infrastructure Development (10 Credits): Focuses on designing and managing network infrastructures, covering both hardware and software aspects of connectivity.
6. Internet of Things (IoT) (10 Credits): Examines IoT architecture, protocols, and applications, teaching learners to integrate IoT systems within existing infrastructures.
7. Artificial Intelligence (10 Credits): Explores AI concepts, including machine learning algorithms and applications in automation and data analysis.
8. Computer-based Research Methods (10 Credits): Teaches research methodologies relevant to computing, focusing on quantitative and qualitative data collection and analysis.

Discover the various pathways and course combinations available to tailor your learning experience and achieve your goals. Click here to explore more information on your options.

Explore the complete curriculum for this course to gain a detailed understanding of the topics covered, learning objectives, and key skills you'll develop. Click here to access the full curriculum.

Guidance on Elective Selection

Learners are encouraged to consult with the Student Advisor Office to choose electives that align with their career goals and maximise both academic and practical performance. The Student Advisor Office provides personalised guidance to ensure optimal elective selections for skill development and professional growth.

Assessment and  Regulations 

Assessment Approach

Each module is assessed through a combination of practical assignments, case studies, and research-based projects to measure both theoretical understanding and practical application:

• Written Assignments: Required for each module to assess comprehension and application of computing theories and principles.
• Practical Projects: Involves hands-on tasks that apply technical skills to real-world computing challenges.
• Case Studies: Real-world scenarios where learners demonstrate problem-solving abilities and strategic thinking in computing technologies.

Grading System

Grades are awarded as Pass, Merit, or Distinction:

• Pass: 40%-59%
• Merit: 60%-69%
• Distinction: 70% and above

Completion Requirements

Learners must pass all six units by achieving at least 40% in each. All assessments undergo both internal and external moderation by Awarding Body for quality assurance.

Professional Development and Progression

Progress to Higher-Level Study:

• Pursue a level 8 Doctor of Philosophy (PhD) or Professional Doctorate. This is the next academic step for individuals seeking to contribute original research in their field of expertise.
• Some professionals pursue another master’s degree to specialise in a different area or broaden their expertise.

Employment Opportunities:

This qualification prepares graduates for roles such as:

• IT Project Manager
• Cyber Security Analyst
• Data Scientist
• Software Engineer

Learners gain practical skills and insights applicable to leadership roles in the technology sector, with assignments designed to support career advancement in diverse computing fields.