Master in Applied Computing (BRIDGING MODULE)

The Master in Applied Computing (Bridging Module) at Taylor’s University is designed to foster innovation and cultivate the next generation of technology leaders. The programme aims to develop critical talent for the knowledge economy while enhancing academic-industry partnerships across various disciplines.

Students can specialise in areas such as Artificial Intelligence, Data Science, and the newest track in Cybersecurity. The Artificial Intelligence specialisation covers machine learning, deep learning, and natural language processing, while Data Science focuses on big data analytics, statistical modeling, and data visualization. The Cybersecurity track prepares students to design, defend, and respond to evolving digital threats across systems and networks.

With a limited cohort admitted each intake, participants benefit from close mentorship by experienced faculty, positioning themselves to drive innovation at research laboratories and technology firms.

Entry Requirements

• A Bachelor’s degree (Level 6, MQF) in Computing or related fields with a minimum CGPA of 2.50, as accepted by the HEP Senate.

For other qualifications and certificates (e.g.,Other qualifications equivalent to a Bachelor’s degree , etc..) please contact our educational consultants or submit your application for Admission assessment.

Future Careers

Artificial Intelligence Specialisation

• AI Researcher
• Intelligence Specialist
• Consultant
• AI Data Analyst
• Machine Learning Programmer
• Machine Learning Engineer
• Robotics R&D Engineer
• Machine Vision Engineer
• Artificial Intelligence Analyst
• Deep Learning Scientist

Cybersecurity Specialisation

• Security Analyst
• Data Scientist – Cybersecurity Operations
• Intelligent Cybersecurity Specialists
• Security Operation Center Manager
• Cybersecurity Threat Analyst – Data Science
• Cybersecurity Data Scientist
• AI Cybersecurity Engineers

Data Science Specialisation

• Data Engineers
• Data Analyst
• Business Analyst
• Data Scientist
• Chief Technology Officer (CTO)
• Data Analytics Manager
• Business Analyst Manager
• Data Innovation Manager
• Machine Learning Scientist
• Business Process Engineer
• Data Wrangler / Munger / Miner
• Business Intelligence Manager
• Analytics & Reporting Manager
• Decision Analytics Manager