The Future of Data
Digitalisation has increased the availability, use and value of data. HDR candidates must be enabled to engage in the effective, efficient and ethical use of data for research purposes. This module develops fundamental awareness and knowledge about key concepts, essential tools and best practises across the lifecycle of data-driven research.
The Future of Data: Data Analytics – Concepts, Principles and Practices
Free of Charge
for eligible students from ATN member universities.
for those in the second half of their PhD studies.
All levels of knowledge and experience in this area
Designed to shape how you think, feel and act in relation to data, this module will increase your ability to navigate and prepare for the demands of professional roles in our data-driven world.
This module provides a series of self-directed learning experiences and facilitated workshops designed to increase your awareness and adoption of useful practices for the effective, efficient and ethical use of data.
It scaffolds 8 topical categories in a sequence of self-paced and/or blended-learning workshop sessions:
- Concepts, Drivers & Trends: Defining key ideas and principles relating to data, analytics and modelling. [self-paced]
- Privacy, Security, Ethics [self-paced]
- Responsible Data Management [self-paced]
- From Question to Data to Insights [self-paced]
- Data Analytics Toolkit: Introducing principles, aids and insights for coding and analytics by syntax. [self-paced]
- Start to Code: Overview and hands-on Python, markdown, Jupyter notebooks and Kaggle. [blended: self-paced + interactive workshop]
- Explore, Describe, Visualise: Convert and communicate data through graphic representation. [blended: self-paced + interactive workshop]
- Tests, Model, Predict: Demonstrating basic analytical computations using the Analytics Toolkit. [blended: self-paced + interactive workshop]
Upon completing this module you will be able to:
- Understand key concepts, drivers and trends as they relate to data analytics as a phenomenon and profession
- Demonstrate more autonomy and authoritative judgement toward responsible and effective data management
- Carry out basic yet powerful data transformations in Python and confidently continue to grow your skills