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  • Advanced Data Analytics for Cybersecurity
MICROCREDENTIAL

Advanced Data Analytics for Cybersecurity

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$1,595.00

START DATE

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MODE

Online

DURATION

10 wks

COMMITMENT

Avg 5 hrs/wk

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Designed as an introduction to machine learning in the field of cybersecurity, this course focuses on machine learning technologies and their potential vulnerabilities – along with cybersecurity tools and solutions.

About this microcredential

This microcredential combines big data capabilities with threat intelligence to help detect, analyse and alleviate insider threats and targeted attacks from external bad actors and persistent cyber threats. It covers key topics including statistical methods for identifying patterns in data and making inferences and other intelligent technologies that derive cybersecurity issues from data.

Participants will be introduced to machine learning technologies for cybersecurity and the most common approach to standard process for data analytics. This microcredential offers practice in advanced technologies of data analytics in cybersecurity, identifying security risks, threats and vulnerabilities to corporate computers and networks.      

Key benefits of this microcredential

  • An end-to-end introduction to cybersecurity in machine learning – build on your understanding of data analytics from a cyber perspective.
  • Develop your understanding of key technologies and concepts along with hands-on activities and case studies to explore real algorithms, attacks and threats.
  • Complete as a self-contained course, or as a potential pathway to future postgraduate study.

This microcredential aligns with the 2-credit point subject, Advanced Data Analytics for Cybersecurity (42896) in the Master of Information Technology (C04295).

This microcredential may qualify for recognition of prior learning at this and other institutions.

Digital badge and certificate digital badge example for UTS Open short courses

A digital badge and certificate will be awarded upon successful completion of the relevant assessment requirements and attainment of learning outcomes of the microcredential.  

Learn more about UTS Open digital badges.

Who should do this microcredential?

This microcredential is accessible to professionals from a wide range of sectors and backgrounds who have completed our Data Analytics for Cybersecurity Foundations microcredential, or who otherwise have foundational professional experience in the field.

UTS microcredentials are developed for professionals with the capacity to undertake postgraduate tertiary education.

Price

Full price: $1,595.00 (GST-free)*

*Price subject to change. Please check price at time of purchase. 

Enrolment conditions

Course purchase is subject to UTS Open Terms and Conditions.

Additional course information

Course outline

In this course, you will meet and work with a dedicated course facilitator who will support your learning and engagement with teaching resources designed by the lead academic and team of experts from the Faculty of Engineering and IT.

The course is structured into four modules. Each module comprises self-study materials and facilitated online sessions. The four modules and key topics covered are:

Module 1 - Supervised machine learning for cybersecurity I

  • This module introduces machine leaning, deep learning and an overview of supervised machine learning algorithms from a cybersecurity perspective.

Module 2 - Supervised machine learning for cybersecurity II

  • This module presents an in-depth case study of attacks on supervised machine learning technologies, in order to explore their potential vulnerabilities to cyber risks.

Module 3 - Unsupervised machine learning for cybersecurity I

  • This module provides an overview of unsupervised machine learning algorithms, including reinforcement learning and federated learning, from a cybersecurity perspective.

Module 4 - Unsupervised machine learning for cybersecurity II

  • This module presents an in-depth case study of attacks on unsupervised machine learning technologies, to explore their potential vulnerabilities to cyber risks.

This course is delivered in a scheduled format over ten weeks.

Each week (during weeks 1 to 8) you will participate in an online session where you will have the chance to apply what you've learned, ask questions and hear from other participants who are taking the course with you. The workshops are led by the course facilitator.

Weeks nine and ten are planned to give you time to complete the final assignment, with support and scheduled Q&A sessions provided.

Course delivery

This course includes weekly, live, one-hour online tutorials and one-hour weekly Q&A sessions facilitated by an expert UTS academic, supporting self-study and online learning activities.

Case studies of real-world applications illustrate applications of key tools and techniques. The workshop sessions focus on hands-on activities and examples. Regular formative quizzes throughout the course will allow participants to gauge their progress.

Course learning objectives

Upon successful completion of this course, you will be able to detect and analyse cyber-attacks using data analytics.

Assessment

The graded assessment task is an individually written assessment on spam data analysis. This assignment includes reflection on individual practical work on spam data analysis (pre-processing and transformation) for cybersecurity, with artefacts (screenshots/outputs) of the practical work to be submitted in the report.

Length: 2,500 words      

Requirements

Mandatory

  • Participants require basic mathematical proficiency (linear algebra and statistics) and some programming experience in Python.
  • To complete this online course, you will need a personal computer with adequate internet access and sufficient software and bandwidth to support web conferencing. You will also require an operating system with a web browser compatible with Canvas and the currently-supported version of Python. 

Contact us

For any questions about enrolment or payment, please contact UTS Open Support at  support@open.uts.edu.au  

For any questions about course content, delivery, or progression, please contact the The Faculty of Engineering and IT at FEITshortcourses@uts.edu.au

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