COURSES OFFERED BY INTERSECT

This hands-on training is designed to familiarize you further with the SPSS data analysis environment. In this session, we will traverse into the realm of inferential statistics, beginning with linear correlation and reliability.

Python has deservedly become a popular language for scientific computing. It has all the friendly features and conveniences you’d expect of a modern programming language, and also a rich set of libraries for working with data.

Tableau is a powerful data visualisation software that can help anyone see and understand their data. With the features to connect to almost any database, drag and drop to create visualizations, and share with a click, it definately makes thing easier.

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.

MATLAB is an incredibly powerful programming environment with a rich set of analysis toolkits. But what if you’re just getting started – with MATLAB and, more generally, with programming?

In this introductory course you will learn the basics of databases and SQL using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.

We’ll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data.

In all fields of research we are being confronted with a deluge of data; data that needs cleaning and transformation to be used in further analysis. This webinar demonstrates the effective use of programming tools for an initial analysis of COVID-19 datasets, with examples using both R and Python.

The Unix environment is incredibly powerful but quite daunting to the newcomer. Command line confidence unlocks powerful computing resources beyond the desktop, including virtual machines and High Performance Computing. It enables repetitive tasks to be automated.

Many research fields can benefit from automation and programmatic techniques, ranging from the humanities and social sciences through biomedical sciences and engineering. The tools and techniques taught in this workshop will be of use to anyone who currently uses a computer for their research.