R is a programming language and environment for working with data, with flexible tools for readying a dataset for analysis, creating multi-faceted visualisations, and fitting models or performing statistical tests on it. R is freely available, open source software, and is a popular tool for statisticians and data scientists.
We run a series of different R workshops, including:
- Introduction to R - [workshop materials]
- Reproducible Research in R - [workshop materials]
- Programming and Tidy Data Analysis in R - [workshop materials]
- Linear models in R - [workshop materials]
For more information about this tool, available workshops, and links to our learning resources visit our Toolkit page for R.
Python is a popular general-purpose programming language that is great for working with research data. As one of the most popular programming languages, Python is very versatile, has a simpler syntax than a lot of other languages, supports reproducibility, and can be used in a wide variety of research activities.
We run a series of different Python workshops, including:
- Introduction to Python - [workshop materials]
- Image analysis in Python with SciPy and scikit-image - [workshop materials]
- TensorFlow and Machine Learning (Uses and requires previous experience with Python) - [workshop materials]
- Introduction to Web Scraping (Uses and requires previous experience with Python) - [workshop materials]
- AI with Deep Learning (Uses and requires previous experience with Python)
- Deep Learning for Natural Language Processing (Uses and requires previous experience with Python)
For more information about this tool, available workshops, and links to our learning resources visit our Toolkit page for Python.
OpenRefine is a standalone, open-source desktop application that enables the collection, manipulation, transformation and standardisation of incomplete or inconsistent data without affecting the data’s original structure. OpenRefine offers a wide variety of functions to collect, normalise and transform data.
We run a beginner level OpenRefine workshop:
- Cleaning data with OpenRefine - [workshop materials]
For more information about this tool, available workshops, and links to our learning resource visit our Toolkit page for OpenRefine.
While the Graphical User Interface makes your computer easy to use, it does not give you full control over all its possible functions. Using the Command Line Interface (CLI) to control the Shell, in contrast, enables you to carry out a huge range of tasks, covering all of the functions of which the computer is capable. Harnessing the Shell through a CLI is particularly useful for dealing with large volumes of data or when you need to automate a process.
We run a series of different Unix Shell workshops, including:
- Introduction to Unix Shell and command line - [workshop materials]
For more information about this tool, available workshops, and links to our learning resources visit our Toolkit page for Unix Shell.
High-Performance Computing is the use of extremely powerful computers for running complex computational tasks that would take days, months or even years to complete on a standard computer. It may refer to the use of a supercomputer, a single high-powered unit with many processors, or a group of powerful computers linked together to form a 'cluster'.
Specialised programming is required to configure programs to run in this way so that they can make full use of the combined processing power available.
- We currently run an Introduction to High-Performance Computing workshop - [workshop materials]
For more information about this tool, available workshops, and links to our learning resources visit our Toolkit page for High-Performance Computing.
TensorFlow is used to develop machine learning applications. Instead of explicitly telling the computer what to do, machine learning uses statistical and mathematical models on large data sets to determine patterns, similarities and comparisons in the data.
TensorFlow is an open source library developed by Google and is most commonly used with Python.
- We currently run an Introduction to TensorFlow workshop - [workshop materials]
For more information about this tool, available workshops, and links to our learning resources visit our Toolkit page for TensorFlow.
This hands-on introductory workshop aims to teach researchers how to use REDCap as the main data collection tool for health research. REDCap is a web application, provided free by the Helix team at Monash University to allow a researcher to collect health data, create surveys, randomise patients, setup longitudinal study in a secure environment. This workshop will teach you how to setup your study in REDCap from the ground-up.
At the end of the workshop, students will be able to:
- Understand REDCap navigation
- Setup a longitudinal with PROMs
- Create and edit data collection form or case reporting form
- Perform data entry
- Manage users
- Perform data quality check
- Setup surveys
Data organisation supports good research by allowing researchers to identify and quickly retrieve data. The presentation will focus on Google Drive and Windows File Explorer to demonstrate data organisation concepts.
The presentation will cover:
- The importance of systematic file naming and how to develop filenames
- How renaming files and folders can alter their behaviour
- File and folder sorting to help researchers find data
- A simple backup strategy
- The importance of version control and how to record file versions
- Important questions to ask before embarking on data organisation
Who can register for a workshop
Our workshops are open to all Monash University research and professional staff, and graduate research students (PhD and Masters by Research).
Registering for a workshop
Workshop registration is available through myDevelopment. This aligns with myPlan and training records for staff, and enables more streamlined processes for assigning credit towards the Monash Doctoral Program for Graduate Research students.
To browse our upcoming workshops, please see our Events page. Alternatively, staff and graduate research students can search for upcoming Data Fluency workshops on myDevelopment:
- Log into myDevelopment from your myMonash portal.
- Type "Data Fluency" or the software you are interested in (eg. "python") into the search box to find a list of available workshops.
Looking for something else?
There is a wide range of tools you can use for your research, depending on what you want to achieve. These tools are often available through the University's Software Catalogue. For training opportunities and learning resources on how to use these tools, Monash staff and postgraduate students may wish to look in myDevelopment, LinkedIn Learning (formerly Lynda.com), or check to see what your faculty is offering.
Data Fluency continues to grow its range of available workshops in these tools.
Suggest a workshop!
Please let us know if there is a topic or tool you think we should add to our growing list of available workshops.