• Class Number 4181
  • Term Code 3430
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Kerry Taylor
    • Dr Kerry Taylor
  • Class Dates
  • Class Start Date 19/02/2024
  • Class End Date 24/05/2024
  • Census Date 05/04/2024
  • Last Date to Enrol 26/02/2024
SELT Survey Results

Massive amounts of data are being collected by public and private organisations, and research projects, while the Internet provides a very large source of information about almost every aspect of human life and society. Analysing such data can provide significant benefits to an organisation. This course provides a practical focus on the technology and research in the area of data mining. It focuses on the algorithms and techniques and less on the mathematical and statistical foundations.

Learning Outcomes

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

  1. Critically analyse and justify the steps involved in the data mining process.
  2. Anticipate and identify data issues related to data mining.
  3. Test and apply the principal algorithms and techniques used in data mining.
  4. Justify suitable techniques to use for a given data mining problem.
  5. Appraise and reflect upon the results of a data mining project using suitable measurements.
  6. Reflect upon ethical and social impacts of data mining.

Research-Led Teaching

The course is updated annually to account for some research progress over the previous year. There is one topic on the course, knowledge graph mining, that particularly reflects very recent research, including that conducted by the course convenor with other ANU colleagues.

Examination Material or equipment

Please see course outline on course Wattle site. Exams will be held using ANU computing labs.

Required Resources

Please see course outline on course Wattle site.

Whether you are on campus or studying online, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

Staff Feedback

Students will be given feedback on assignments in the following forms in this course:

  • written individual comments as a marked-up rubric and/or individual remarks.
  • verbal comments if requested via procedures notified at the time of assessment return
  • summary feedback, including mark distribution, to whole class.

Students will be given feedback on the weekly quizzes by immediate marking, with brief written explanation of wrong answers, and the opportunity to reattempt.

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

This course introduces fundamental concepts that could potentially be addressed by certain Generative AI tools (e.g., ChatGPT). Hence, the use of any Generative AI tools is not permitted in graded assessments within this course.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to Data Mining Please see detailed course outline and weekly course schedule published on wattle after enrolment.
2 Foundation Concepts
3 Research
4 Data Warehousing
5 Association Mining
6 Classification and Prediction
7 Classification and Prediction
8 Cluster Analysis
9 Outlier Detection
10 Specialist Topics
11 Text and Web Mining
12 Semantic Web and Knowledge Graphs

Tutorial Registration

See the Timetable webpage.

Assessment Summary

Assessment task Value Due Date Learning Outcomes
Weekly online quiz 1 % * 1,2,3,4,5,6
Assignment 1 20 % 11/03/2024 1,6
Assignment 2 25 % 06/05/2024 1,2,3,4,5
Final Exam 3 hours 54 % * 1,2,3,4,5,6

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


Formal final exam to be held during exam period on campus.

Assessment Task 1

Value: 1 %
Learning Outcomes: 1,2,3,4,5,6

Weekly online quiz

Distributed on Wattle. Due 11:59pm Wednesdays of the following week. Return date: immediate on completion.

Assessment Task 2

Value: 20 %
Due Date: 11/03/2024
Learning Outcomes: 1,6

Assignment 1

Hurdle assessment 30% min to pass. Return date: 2 weeks after due date.

Assessment Task 3

Value: 25 %
Due Date: 06/05/2024
Learning Outcomes: 1,2,3,4,5

Assignment 2

Hurdle assessment: 30% min to pass. Return date: 2 weeks after due date.

Assessment Task 4

Value: 54 %
Learning Outcomes: 1,2,3,4,5,6

Final Exam 3 hours

To be held in formal exam period. Hurdle assessment: 40% min to pass.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Late submission not permitted. A mark of 0 will be awarded if submitted after the due date without an extension.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Returning Assignments

via Wattle gradebook. A summary of general feedback overall will also be distributed.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments


Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Kerry Taylor

Research Interests

Dr Kerry Taylor

Thursday 16:00 17:00
Dr Kerry Taylor

Research Interests

Dr Kerry Taylor

Thursday 16:00 17:00

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions