HPC at UniSA
UniSA provides a powerful High Performance Computing (HPC) service to support the demanding computational needs of its researchers and research degree candidates.
Solve complex computational problems faster on the HPC using:
- Large numbers of CPU cores
- High amounts of memory
- Specialist research software
Learn more below
Software
Find software to help you to work with your data.
- SPSS Software Licensing page
Widely used for statistical analysis in social sciences, as well as other discipline areas such as Health Sciences, Marketing, and Education. The University has a licence agreement with SPSS that allows use of this software at no charge. - NVivo Software Licensing
For qualitative data analysis. NVivo gives you a place to organize, store and retrieve your data so you can work more efficiently, save time and rigorously back up findings with evidence - Qualtrics XM
Design your survey with an intuitive drag-and-drop survey tool, powerful logic, 100 plus question types, and pre-built survey templates. Qualtrics is available fully licensed to all UniSA staff, researchers and HDR students.
- R
Widely used for statistical analysis in social sciences, as well as other discipline areas such as Health Sciences, Marketing, and Education. The University has a licence agreement with SPSS that allows use of this software at no charge. - Python
A general purpose and high level programming language.
Workshops and tutorials
- NVivo online tutorialsA suite of videos for PC and Mac which allows you to work at your own pace.
The Library does not provide support for NVivo software. Please seek advice from your school or research centre.
- Learning NVivo - LinkedIn Learning tutorialsBeginner level tutorial (1hr 10m)
- NVivo 2018 Essentials - LinkedIn Learning tutorialBeginner level tutorial (1hr 23m)
- NVivo by QSR YouTube channelDiscover QSR International's NVivo for Windows and NVivo for Mac qualitative data analysis software. Learn more about NVivo software by watching tutorials, how-to videos, recorded eSeminars and eDemos.
- Learn to use Qualtrics for researchThis series of 6 videos will teach you the basics of building and distributing a survey project, as well as how to report on your research data.
- Qualtrics training siteA suite of on-demand training courses from Qualtrics
- Qualtrics support guidesA range of comprehensive how-to pages on all the main features and functionality of the platform.
- Mathematical Biostatistics Boot Camp 1John Hopkins University
- Mathematical Biostatistics Boot Camp 2John Hopkins University
The Library does not provide support for SPSS software. Please seek advice from your school or research centre.
- SPSS Statistics Essential Training - LinkedIn Learning tutorialBeginner level tutorial (4hr 57m)
- R Programming 101A suite of videos which allow you to work at your own pace.
- R for data science: Lunchbreak lessons - LinkedIn LearningThis weekly series reviews the language features, development tools and libraries that will make you a more productive R programmer. Intermediate level tutorial (5h 24m)
- Learning R - LinkedIn LearningIntroduces the R statistical processing language, including how to install R on your computer, read data from SPSS and spreadsheets, and use packages for advanced R functions. Beginner level tutorial (2h 25m)
- Learn PythonA full introduction into all of the core concepts in Python (4h 26m)
- Learning Python - LinkedIn LearningProvides an overview of the installation process, basic Python syntax, and an example of how to construct and run a simple Python program. Learn to work with dates and times, read and write files, and retrieve and parse HTML, JSON, and XML data from the web. Beginner level course (2h 11m)
- Python: Data analysis - LinkedIn LearningIf you're going to work with big data using Python, you'll be definitely using Pandas and NumPy, the third-party packages designed specifically for data analysis. This course provides an opportunity to learn about them, including how to set up your analysis environment, using data containers, and the power of arrays, indexing, and DataFrames in NumPy and Pandas. Intermediate level course (2h 16m)