New Zealand Diploma in Information Systems

New Zealand Skills and Education College

Subject area

Information Systems

Qualification

Check out Fees Free to see whether you are eligible for a year of fees-free study or two years industry training. Contact your provider to confirm your study options meet the criteria.

Entry requirements

None.

About the course

What can I expect out of this qualification?

The purpose of this stranded qualification is to provide Aotearoa New Zealand with people who have attained a range of specialist professional and technical Information Systems (IS) skills and current ways of working including Agile and DevOps. It will prepare people for employment in an intermediate level IS role in a range of organisational contexts, operating both independently and as part of a team.

Businesses, organisations and communities will benefit from having IT professionals who are experienced and qualified in specific contexts within IS, and an ability to work in Agile development environments. This qualification provides an opportunity for people wanting to broaden their skills and knowledge in IS, which may include people already working in the IT sector, as well as others wishing to enter it.

Graduates of this qualification will have the information systems skills that will enable them to contribute to society, supporting digital proficiency and using their digital capability in a range of community and voluntary areas, and proceed to further study.

Graduates of the Business Analysis strand will have a focus on business analysis and managing software development processes.

Graduates of the User Experience strand will have a focus on human computer interaction (HCI).

Graduates of the IT Project Management strand will have a focus on the tools and techniques used in IT project management.

Graduates of the Information Systems Innovation strand will have a focus on innovation to address organisational needs and opportunities.

Graduates of the Data Analysis strand will have a focus on the tools and techniques used in the analysis of big data.