« Data and Analysis


Thu 18 Nov 2021 - Mon 22 Nov 2021

02:00PM

3 Sessions

Online

Description 

This micro-credential examines some of the business and legal consequences of data breaches and cyber attacks. Typologies and examples will provide context to the nature and risk associated with data systems in the context of breach and attack. It will explore the interaction of different legal systems and jurisdictions.

Topics 

  1. Introduction: Data breaches, cyber attacks and their consequences.
  2. Compliance and Mitigating Legal and Technological Risk and the Cloud.
  3. Breach notification obligations and responding to a data breach.
  4. Accessing cloud data and law enforcement

Learning outcomes 

Upon successful completion, enrolees will have the knowledge and skills to:

  1. Demonstrate an ability to understand the complex issues stemming from a data breach including the legal requirements and potential liabilities and the consequences of a breach
  2. Evaluate legal and policy issues in relation to the re-purposing of private and confidential data for law enforcement purposes
  3. Critically analyse the intersections with differing policy agendas and identify the different interests underlying law enforcement access to data in the context of the provision of cloud services
  4. Engage in discussions on the application of key requirements to new technologies and the ongoing policy debates regarding the mitigation of cyber risks

Indicative assessment 

1,200 word research piece: 75%; links to Learning Outcomes 1, 2, 3

400 word-equivalent activity; 25%; links to Learning Outcomes 2, 4

Assumed knowledge 

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as a stand-alone course or as part of a "stack". The three M-Cs proposed for this “Ninian Stephen Cyber and the Data Professional” stack are:

  1. Data Privacy and Confidentiality - Associate Professor Philippa Ryan
  2. Systems Integrity and Consequences of Breach - Associate Professor Will Bateman
  3. Emotional Artificial Intelligence and the Law - Dr Damian Clifford

Details 

Course Code: DATA17

Workload: 43 hours 

  • Contact hours: 9 hours
  • Individual study and assessment: 34 hours

ANU unit value: 2 units

AQF Level: 9

Contact: Associate Professor Will Bateman, ANU College


This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

No dates are currently scheduled.

Description 

The aims of this micro-credential is to equip enrollees with the skills and confidence to operate in the world of ‘big data.’ The micro-credential will take a social science perspective and to discuss the role of social science and theory in analysing and interpreting ‘big data.’ The micro-credential will not be technical, but rather use key examples of ‘big data’ being used to inform policy to help motivate and engage with the issues. Enrollees will become familiar with some of the technological options and constraints in the storage and analysis of ‘big data’.

Topics 

  1. Introduction to data linkage
  2. Analysis of linked and transactional data
  3. Combining linked and survey data

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Explain the key concepts of data linkage
  2. Outline the strengths and weaknesses of existing administrative datasets from an analysis or policy perspective
  3. Identify the appropriate analytical technique for analysis of linked or administrative data
  4. Discuss some of the main assumptions underlying different techniques;
  5. Design or critique an analysis plan

Indicative assessment 

Assignment 1 – Introductions and identification of data analysis questions (500 words, 20% of final mark) LO: 1, 2

Assignment 2 – Analysis plan (1,500 words, 80% of final mark) LO: 3, 4, 5, 6

Assumed knowledge 

Completion of ANU Micro-credential Data Analysis and Interpretation (or equivalent).

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as part of a stack by completing Data Analysis and Interpretation.

Details 

Course Code: DATA23

Workload: 21 hours 

  • Contact hours: 7 hours
  • Individual study and assessment: 14 hours

ANU unit value: 1 unit

AQF Level: 8

Contact: Professor Nicholas Biddle

This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

No dates are currently scheduled.

Description 

Microsimulation modelling in this course relates to the simulation of the Australian tax and benefit system on actual persons and households using survey data. The simulations are used for the purpose of understanding existing current and alternative policies in Australia.

Microsimulation modelling is used heavily by researchers and policy analysts in Government but increasingly in academia and the private sector. Microsimulation modelling offers the researcher the capability to understand complex systems such as the tax and transfer system in Australia by simulating the rules of these systems on actual persons and households. By working at the individual level this technique offers insights to policy that is otherwise not feasible.

Recent examples of microsimulation modelling use in Australia include the modelling of the 2014-15 and 2015-16 Federal Budgets. Each of these budgets proposed a complex array of new or altered policies that impact on the disposable incomes and work incentives of Australians. This analysis enabled a full understanding of the winners and losers from the budget in what is called a ‘distributional analysis’. Microsimulation modelling can also incorporate behavioural impacts through altered economic behaviour or dynamic impacts through time.

Topics 

  1. Simulating the tax and transfer system
  2. Simulating population change
  3. Analysing policy change using microsimulation techniques

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Explain the key concepts of microsimulation modelling
  2. Outline the strengths and weaknesses of existing models from an analysis or policy perspective
  3. Discuss some of the main assumptions underlying different techniques
  4. Design or critique a microsimulation model

Indicative assessment 

Assignment 1 – Introductions and identification of data analysis questions (500 words, 20% of final mark) LO: 1, 2

Assignment 2 – Analysis plan (1,500 words, 80% of final mark) LO: 3, 4, 5, 6

Assumed knowledge 

Completion of ANU Micro-credential Data Analysis and Interpretation (or equivalent).

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as part of a stack by completing Data Analysis and Interpretation.

Details 

Course Code: DATA26

Workload: 21 hours 

  • Contact hours: 7 hours
  • Individual study and assessment: 14 hours

ANU unit value: 1 unit

AQF Level: 8

Contact: Associate Professor Benjamin Phillips

This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

No dates are currently scheduled.

Description 

The purpose of the micro-credential is to increase professional baseline literacy in cyber law in order to equip practitioners and policy experts with the tools and knowledge to better manage the intersection between the law, legal practice and technology.

Topics 

  1. The Proliferation of Data Privacy Frameworks
  2. Global Data Privacy and Trade
  3. Data Privacy and Commercial Surveillance
  4. Invasions of privacy, individual causes of action and breach of confidence

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Demonstrate an ability to investigate the complex issues stemming from the proliferation of technologies reliant on intensive personal information/data processing
  2. Evaluate legal and policy issues in relation to new uses for private and confidential data
  3. Critically analyse the intersections with differing policy agendas and identify the different interests and underlying data governance
  4. Engage in discussions on the application of key requirements to new technologies and the ongoing policy debates

Indicative assessment 

1,200 word research essay: 75%; links to Learning Outcomes 1, 2, 3

400 word-equivalent activity: 25%, links to Learning Outcomes 2, 4

Assumed knowledge 

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as a stand-alone course or as part of a "stack". The three M-Cs proposed for this “Ninian Stephen Cyber and the Data Professional” stack are:

  1. Data Privacy and Confidentiality - Associate Professor Philippa Ryan
  2. Systems Integrity and Consequences of Breach - Associate Will Bateman
  3. Emotional Artificial Intelligence and the Law - Dr Damian Clifford

Details 

Course Code: DATA06

Workload: 43 hours 

  • Contact hours: 9 hours
  • Individual study and assessment: 34 hours

ANU unit value: 2 units

AQF Level: 9

Contact: Associate Professor Philippa Ryan, Associate Professor, ANU College of Law


This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

No dates are currently scheduled.

Description 

This micro-credential examines some of the legal and emotional consequences of using artificial intelligence systems in business and government. It explores emotional AI or affective computing, which is being used to develop machines that are capable of reading, interpreting, responding to, and imitating human affect.

Topics 

  1. Introduction to Emotional Artificial Intelligence
  2. Emotional Artificial Intelligence and the Law
  3. Personal information and sensitive inferences
  4. New developments in AI and the implications for society

Learning outcomes 

Upon successful completion, enrollees will have the knowledge and skills to:

  1. Demonstrate an ability to understand the complex legal issues associated with the developments in Emotional Artificial Intelligence
  2. Evaluate legal and policy issues in relation to the deployment of Emotional AI in practice
  3. Critically analyse the intersections with differing policy agendas and identify the different interests underlying the moves to regulate AI, and in particular emotional AI
  4. Engage in discussions on the application of key requirements to new technologies such as emotional AI and the ongoing policy debates

Indicative assessment 

1,200 word research essay: 75%; links to Learning Outcomes 1, 2, 3

400 word-equivalent activity; 25%; links to Learning Outcomes 2, 4

Assumed knowledge 

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as a stand-alone course or as part of a "stack". The three M-Cs proposed for this “Ninian Stephen Cyber and the Data Professional” stack are:

  1. Data Privacy and Confidentiality - Associate Professor Philippa Ryan
  2. Systems Integrity and Consequences of Breach - Associate Professor Will Bateman
  3. Emotional Artificial Intelligence and the Law - Dr Damian Clifford

Details 

Course Code: DATA07

Workload: 43 hours 

  • Contact hours: 9 hours
  • Individual study and assessment: 34 hours

ANU unit value: 2 units

AQF Level: 9

Contact: Dr Damian Clifford


This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

No dates are currently scheduled.

Description 

The aim of this micro-credential is to equip enrollees with the skills and knowledge to engage with empirical research on race, racism and inequities either directly as a researcher, or as a policy maker critically engaging with the most recent research.

Topics 

  1. Understanding ‘race’ and ethnicity
  2. Understanding racism as a fundamental cause of inequities
  3. Principles of quantitative research design for race, racism and inequities research
  4. Principles of data analysis for race, racism and inequities research
  5. Interpreting research on race, racism and inequities for decision making

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Specify a research question related to race, racism and inequities that is answerable using quantitative empirical methods
  2. Communicate and critique existing quantitative research on race, racism and inequities in a rigorous manner.
  3. Understand the assumptions, strengths and limitations of research on race, racism and inequities
  4. Understand approaches to analysis of race, racism and inequities research
  5. Design or critique a research study on race, racism and inequities

Indicative assessment 

Assignment 1 – Introductions and identification of research question (500 words, 20% of final mark) LO: 1, 2

Assignment 2 – Research design (1,500 words, 80% of final mark) LO: 3, 4, 5

Assumed knowledge 

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as a stand-alone course.

Details 

Course Code: DATA15

Workload: 22 hours 

  • Contact hours: 7 hours
  • Individual study and assessment: 15 hours

ANU unit value: 1 unit

AQF Level: 8

Contact: Associate Professor Naomi Priest

 

This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

No dates are currently scheduled.

Description 

The aim of this course is to equip enrollees with the skills and knowledge to engage with empirical research either directly as a researcher, or as a policy maker critically engaging with the most recent research.

Topics 

  1. Designing a quantitative research project
  2. Incorporating qualitative insights
  3. Principles of sampling
  4. Principles of survey design
  5. Using administrative and linked datasets

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Specify a research question related to the policy process that is answerable using empirical methods
  2. Communicate and critique existing research in a rigorous manner
  3. Understand the assumptions, strengths and limitations of the main empirical techniques for policy design
  4. Understand the different forms of sampling design and their strengths/limitations
  5. Design or critique a survey or data collection methodology

Indicative assessment 

Assignment 1 – Introductions and identification of research question (500 words, 20% of final mark) LO: 1, 2

Assignment 2 – Research design (1,500 words, 80% of final mark) LO: 3, 4, 5

Assumed knowledge 

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as a stand-alone course.

Details 

Course Code: DATA16

Workload: 22 hours 

  • Contact hours: 7 hours
  • Individual study and assessment: 15 hours

ANU unit value: 1 unit

AQF Level: 8

Contact: Professor Nicholas Biddle

 

This Micro-credential is taught at a graduate level.  This is not an AQF qualification.