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:
- Critically analyse and justify the steps involved in the data mining process.
- Anticipate and identify data issues related to data mining.
- Test and apply the principal algorithms and techniques used in data mining.
- Justify suitable techniques to use for a given data mining problem.
- Appraise and reflect upon the results of a data mining project using suitable measurements.
- 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 and some tutors.
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.
Recommended Resources
Please note, 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 | Data Warehousing | |
4 | Association Mining | |
5 | Classification and Prediction | |
6 | Classification and Prediction | |
7 | Cluster Analysis | |
8 | Catchup ( for 3 public holidays) | |
9 | Outlier Detection | |
10 | Ensembles and Time | |
11 | Text Mining | |
12 | Semantic Web and Knowledge Graphs |
Tutorial Registration
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Assessment Summary
Assessment task | Value | Learning Outcomes |
---|---|---|
Weekly online quiz | 1 % | 1,2,3,4,5,6,7 |
Assignment 1 | 20 % | 1,6,7 |
Assignment 2 | 29 % | 1,2,3,4,5 |
Final Exam 3 hours | 50 % | 1,2,3,4,5,6,7 |
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
Policies
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:
- Academic Integrity Policy and Procedure
- Student Assessment (Coursework) Policy and Procedure
- Extenuating Circumstances Application
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
- Code of practice for teaching and learning
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.
Participation
Attendance at labs is not assessed. However, in-lab learning is essential and non-attendance is very likely to be reflected in course marks.
Examination(s)
Formal final exam to be held during exam period on campus.
Assessment Task 1
Learning Outcomes: 1,2,3,4,5,6,7
Weekly online quiz
Distributed on Wattle. Due 11:59pm Wednesdays of the following week. Return date: immediate on completion.
Assessment Task 2
Learning Outcomes: 1,6,7
Assignment 1
Hurdle assessment 30% min to pass. Return date: 2 weeks after due date for on-time submissions.
Assessment Task 3
Learning Outcomes: 1,2,3,4,5
Assignment 2
Hurdle assessment: 30% min to pass. Return date: 2 weeks after due date for on-time submissions.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5,6,7
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. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.
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
None.
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).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Accessibility for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents all ANU students
Convener
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Research Interestsmachine learning, knowledge graphs, semantic web |
Dr Kerry Taylor
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