Lincoln University

What you'll study

The programme combines advanced coursework in contemporary computing topics with a substantial applied project or research component. Core themes include software engineering and architecture, data management and analytics, machine learning and artificial intelligence, cloud and distributed systems, cybersecurity fundamentals, and practical aspects of systems integration and deployment.

• Advanced Software Development: software design patterns, testing, DevOps practices and scalable application development.
• Data Analytics and Databases: relational and NoSQL databases, data modelling, data pipelines and exploratory data analysis.
• Machine Learning and AI: supervised and unsupervised methods, model evaluation, and applied machine learning for practical problems.
• Cloud and Distributed Systems: cloud services, containerisation, microservices and orchestration concepts for deployed systems.
• Security and Professional Practice: basic security principles, risk assessment, project management and ethics in computing.
• Applied Project / Dissertation: an individual or sometimes industry‑linked project that applies learned techniques to a real problem, producing a software artefact and a formal report or thesis.

Teaching typically mixes lectures, laboratory work, group projects and supervised research. Assessment includes programming assignments, project reports, presentations and the final applied project or dissertation.

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in computer science, information technology, software engineering or a closely related discipline. Candidates with a bachelor’s degree in another discipline plus substantial relevant computing work experience or a recognised conversion qualification may also be considered. International applicants must satisfy the University’s English language requirements.

Selection may take into account prior academic performance, relevant professional experience and the applicant’s ability to undertake an advanced project. Where applicants do not meet the formal academic requirements, the University may require evidence of programming competency or completion of bridging courses.

Career prospects

Graduates leave prepared for technical and applied roles across the technology sector and in organisations that use computing to solve domain problems. Common career paths include:

• Software developer / engineer in commercial or public sector organisations.
• Data analyst or data scientist, working with datasets to inform decision‑making.
• Systems architect, cloud engineer or DevOps specialist responsible for designing and operating scalable systems.
• IT consultant or technical project manager delivering solutions for clients.
• Roles in applied domains such as agritech, environmental modelling, GIS and precision agriculture where computing skills are integrated with domain knowledge.
• Further research study (PhD) for those who pursue the dissertation pathway and wish to move into academic or advanced research careers.

Why study at Lincoln University

Lincoln University offers a smaller, collegial campus environment with close student–supervisor contact and opportunities to work on interdisciplinary projects. The Master of Applied Computing emphasises applied outcomes and industry relevance, with options to engage in projects linked to regional businesses and research groups.

Students benefit from hands‑on laboratory facilities, computing resources and access to supervisors experienced in both academic research and professional practice. The University’s strong links with agricultural, environmental and land‑based sectors also create distinctive pathways for applying computing skills to real‑world challenges in areas such as agritech, remote sensing and spatial data analysis.

Overall, the programme is suited to those who want technical depth combined with practical experience and a clear orientation to employability or continued research training.