JST495 Intelligence and Analytics (8)

This subject provides the student with an advanced understanding and mastery of data mining and analytics in the national security, policing and business intelligence contexts. Students will develop a deep understanding of data, and how to interpret patterns in it using various analytical methodologies. Students will also be introduced to and apply a range of prediction technologies and competitive analytical techniques increasingly being used by intelligence officers and investigators. Students will apply these skills to a range of examples including but not limited to: fraud, counter-terrorism, money laundering and other financial crimes. Intelligence practitioners, investigators and managers seeking to develop data mining and analytics capabilities in their organisations will benefit from this subject.

Availability

Session 1 (30)
Online
Manly Campus
Session 2 (60)
Online
Manly Campus

Continuing students should consult the SAL for current offering details: JST495. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

Australian Graduate School of Policing and Security

Learning Outcomes

Upon successful completion of this subject, students should:
  • Explain key intelligence and analytical concepts, data mining including legal and ethical aspects;
  • Demonstrate mastery of contemporary theoretical knowledge and discourse on data mining, analytics and knowledge discovery techniques in the intelligence context;
  • Use a range of analytical tools in supporting tactical/operational analysis and be able to apply appropriate analytical tools to different analytical problems;
  • Collect, analyse, consolidate and synthesise operationally relevant information to provide reports (intelligence reports) that can explain a range of security threats and provide recommendations to address these; and
  • Demonstrates the communication, literacy, numeracy, research, and digital skills required of a competent, professional intelligence analyst.

Syllabus

This subject will cover the following topics:
  • Topic 1 Introduction
  • 1.1 What is data mining and analytics?
  • 1.2 Intelligence and the applications of data mining and analytics
  • Topic 2 Data
  • 2.1 Kinds of data
  • 2.2 How is data collected?
  • 2.3 Fusion of different kinds of data
  • 2.4 Problems with data
  • Topic 3 Knowledge Discovery
  • 3.1 Introduction to knowledge discovery
  • 3.2 Sense making
  • Topic 4 Applying intelligence and analytics to real world problems
  • 4.1 Looking for risk/predictive analysis
  • 4.2 Analytical tools and techniques
  • 4.3 Practical exercises
  • Topic 5 Contempoary issues and problems

The information contained in the CSU Handbook was accurate at the date of publication: January 2020. The University reserves the right to vary the information at any time without notice.

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