Workshop & Events

01/03/2021 - 09:30 to 12:30 | Register
This workshop is an introduction to data structures (DataFrames using the pandas library) and visualisation (using the matplotlib library) in Python.
04/03/2021 - 13:30 to 05/03/2021 - 12:30 | Register
Learn about the fundamental concepts in programming using R and apply them to analyse a sample research dataset. In this live coding workshop we will write programs that produce results, using
11/03/2021 - 09:30 to 12:30 | Register
This workshop is an introduction to data structures (DataFrames) and visualisation (using the ggplot2 package) in R.
15/03/2021 - 13:30 to 16/03/2021 - 12:30 | Register
Develop a working knowledge of Microsoft Excel to manage, analyse and visualise your research data. While this workshop is aimed at novice Excel users, most attendees will walk away with new t
17/03/2021 - 10:00 to 12:00 | Register
The orientation is an important event that provides you with key information to ensure a smooth transition to your research candidature at UNSW.
19/03/2021 - 09:30 to 12:30 | Register
Learn the fundamentals of NVivo including importing data, creating nodes and producing basic visualisations. NVivo allows researchers to simply organise and manage data from a variety of sourc
24/03/2021 - 09:30 to 12:30 | Register
In this workshop, you will explore DataFrames in depth (using the pandas library), learn how to manipulate, explore and get insights from your data (Data Manipulation), as well as how to deal with
25/03/2021 - 09:30 to 12:30 | Register
In this workshop, you will explore different types of graphs and learn how to customise them using two of the most popular plotting libraries in Python, matplotlib and seaborn (Data Visualisation).
26/03/2021 - 09:00 to 16:00
TransCelerate-endorsed GCP training designed to give participants involved in research and trials a thorough understanding of all aspects of Good Clinical Practice and how it applies
29/03/2021 - 09:30 to 12:30 | Register
In this workshop, you will learn how to manipulate, explore and get insights from your data (Data Manipulation using the dplyr package), as well as how to convert your data from one format to anoth