This course aims to extend actuarial students' knowledge of modern analytical tools and techniques beyond those introduced in introductory actuarial courses. It further aims to to teach students how to apply this knowledge in real-life business settings, preparing them for more complex and practice specific applications which will be taught in future courses in their actuarial education.

This subject provides the opportunity for exemption from the requirements of the Data Analytics Principles subject under the Actuaries Institute’s Actuary program. Such exemption depends on the grades attained in the subject.

Learning Outcomes

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

1. Explain where and how their analytical work can add value to the business environment and strategy.
2. Source, interpret, evaluate, prepare and justify data for modelling.
3. Select, compare and justify appropriate predictive analytic techniques for a given business problem.
4. Apply predictive analytic techniques to solve complex estimation and classification problems.
5. Evaluate and compare performance of different models.
6. Communicate findings to a range of audiences.

Research-Led Teaching

The course will address current issues of interest and current approaches to data analytics, using practical examples and case studies.

Examination Material or equipment

Centrally scheduled examinations through Examinations, and will be timetabled prior to the examination period. Please check ANU Timetabling for further information.

Required Resources

Comprehensive lecture slides will be made available on Canvas. The use of R and Word is required for the completion of some assessments in this course. You are assumed to have experience in R and Word from previous courses. R and Word may be used on campus (if computer labs are open) or on the students’ personal computers or laptops. Word is available for free to ANU students through Microsoft Office 365. R and its user interface R Studio are as freely available at the links provided.

Recommended Resources

We will be using some materials from the following books throughout the semester:

(1) R for Data Science , by Wickham and Grolemund

(2) An Introduction to Statistical Learning , by James, Witten, Hastie and Tibshirani

(3) The Elements of Statistical Learning , by Hastie, Tibshirani and Friedman

The electronic versions of these books are freely available online from the corresponding authors. The relevant readings for each week will be specified in lecture time and on Canvas. Other relevant reading and reference material will be made available on Canvas throughout the semester.

Staff Feedback

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

• Self-study feedback in tutorials, quizzes and assignments; 
• Whole of class or individual feedback in-class or online for performance in assignments; 
• Individual feedback on student performance in assessment tasks is available on request from the lecturer or marker; please make an appointment to request this; 
• Individual feedback during consultations with the lecturer/ tutor.

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

Support for Students

The University offers a number of support services for students. Information on these is available online from http://students.anu.edu.au/studentlife/

Communication via Email

If I, or anyone in the School, College or University administration, need to contact you, we will do so via your official ANU student email address, which you need to check regularly. If you have any questions for the teaching and course convenor make sure you email them using your ANU email address. Emails from personal email accounts will not be answered.

Announcements

Students are expected to check the Canvas course site for announcements about this course, e.g. changes to timetables or notifications of cancellations.

Assessment Requirements

As a further academic integrity control, students may be selected for a 15 minute individual oral examination of their written assessment submissions. Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

Scaling

Your final mark for the course will be based on the raw marks allocated for each of your assessment items. However, your final mark may not be the same number as produced by that formula, as marks may be scaled. Any scaling applied will preserve the rank order of raw marks (i.e. if your raw mark exceeds that of another student, then your scaled mark will exceed the scaled mark of that student), and may be either up or down.

Referencing Requirements

In assignments and exams, students must appropriately reference any results, words or ideas that they take from another source which is not their own. A guide can be found

at https://academicskills.anu.edu.au/resources/handouts/referencing-basics.

Co-Teaching

ACST6032 shares the same lecture content with ACST3032, however these cohorts may have separate tutorials and different assessments. The different cohorts of students will also be treated separately in grading and any scaling that is applied.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Introduction to working with data in R
2	Data visualisation and exploratory data analysis
3	Principles of modelling and K-nearest neighbours
4	Predictive model case study
5	Imbalanced dataset and business communication of outcomes	Quiz
6	Linear regression and GLM
7	Shrinkage techniques	Assignment 1 due
8	Tree-based methods
9	Ensemble trees
10	Artificial neural networks	Assignment 2 due
11	Unsupervised learning
12	Modelling applications

Tutorial Registration

Tutorials will be held on campus weekly (starting from week 2). 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.

Tutorial registration will be available two weeks prior to the beginning of the semester and will close at the end of week 1. More details can be found on the Timetable webpage(https://www.anu.edu.au/students/program-administration/timetabling)

Tutorial registration will be available two weeks prior to the beginning of the semester and will close at the end of week 1. More details can be found on the Timetable webpage (https://www.anu.edu.au/students/program-administration/timetabling)

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Quiz	0 %	22/08/2025	22/08/2025	2, 3, 4, 5
Assignment 1	20 %	15/09/2025	26/09/2025	1, 2, 3, 4, 5, 6
Assignment 2	20 %	10/10/2025	24/10/2025	1, 2, 3, 4, 5, 6
Final exam	60 %	30/10/2025	27/11/2025	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

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 ‘Canvas’ 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

Course content delivery will take the form of weekly on-campus lectures (recorded and available via echo360 on Wattle) and weekly on-campus tutorials. Students are expected to have viewed the course notes and recommended readings before classes. Attendance at lectures, workshops and tutorials, while not compulsory, is expected in line with “Code of Practice for Teaching and Learning”, clause 2 paragraph (b). Weekly consultations with the lecturer and the tutor(s) will be conducted either in-person or over Zoom.

Examination(s)

The final examination will be a three-hour on-campus invigilated exam with a mix of short and long answers questions. The final exam is a compulsory piece of assessment and worth 60% of the total assessment. The final exam will be held during the exam period with details to be advised no later than teaching week 10 of the semester. No Dictionaries allowed. The exam is centrally scheduled through Examinations, Graduations & Prizes and it will be timetabled prior to the examination period. Please check ANU Timetabling for further information.

Assessment Task 1

Quiz

The quiz is 35 minutes in duration with 1 attempt permitted.

The quiz covers material from Week 1 to Week 3.

Value: The quiz is worth 0% of the overall grade.

Quiz access and due date: The quiz will be made available on Canvas in Week 5 from 9am (AEST) on Monday, 18 August to 9pm (AEST) on Friday, 22 August.

Return date and feedback: The quiz solution (and grade, if applicable) will be provided upon submission of an attempt or when the quiz closes, whichever comes first. Studentsmay seek additional feedback from the lecturer by appointment/ email.

Assessment Task 2

Assignment 1

Assignment 1 assesses material from Week 1 to Week 5. The assignment, including any relevant details, will be released on Tuesday of Week 6 on Canvas. 

Students are required to use R to perform data analysis and modelling, and prepare a written business report. Assignment submission will consist of a Word or PDF (PortableDocument Format) report uploaded to Canvas to the relevant Assignment activity through Turnitin. Students will be required to electronically sign a declaration as part of thesubmission of the assignment.

Students are expected to complete this assignment individually.

The assignment is non-redeemable. Late submissions will not be accepted without prior permission from the course convenor and students will receive a mark of zero for theassignment if it is submitted after the due date. 

Value: This assignment is worth 20% of the total assessment.

Due date: 9pm (AEST) on Monday, 15 September, Week 7.

Return date: Grades will be uploaded onto Canvas by Friday, Week 8.

Feedback: Assignment solution will be provided on Canvas by Friday, Week 8. Short individual feedback will be provided online for students who did not score full marks. More detailed feedback from the marker may be available by appointment/ email. General feedback may be given to the whole class in lecture/ on Canvas on cohort performance.

Assessment Task 3

Assignment 2

Assignment 2 assesses material from Week 1 to Week 7. The assignment, including any relevant details, will be released on Canvas on Tuesday of Week 8. 

Students are required to use R to perform data analysis and modelling, evaluate and transform information, and prepare a written business report. Assignment submission willconsist of a Word or PDF (Portable Document Format) report uploaded to Canvas to the relevant Assignment activity through Turnitin. Students will be required to electronicallysign a declaration as part of the submission of the assignment.

Students are expected to complete this assignment individually.

The assignment is non-redeemable. Late submissions will not be accepted without prior permission from the course convenor and students will receive a mark of zero for theassignment if it is submitted after the due date. 

Value: This assignment is worth 20% of the total assessment.

Due date: 9pm (AEST) on Friday, 10 October, Week 10.

Return date: Grades will be uploaded onto Canvas by Friday, Week 12.

Feedback: Assignment solution will be provided on Canvas by Friday, Week 12. Short individual feedback will be provided online for students who did not score full marks. Moredetailed feedback from the marker may be available by appointment/ email. General feedback may be given to the whole class in lecture/ on Canvas on cohort performance.

Assessment Task 4

Final exam

The final examination will be a three-hour on-campus invigilated exam with a mix of short and long answers questions. The final exam is a compulsory piece of assessment and worth 60% of the total assessment. The final exam will be held during the exam period with details to be advised no later than teaching week 10 of the semester. No Dictionaries allowed. The exam is centrally scheduled through Examinations, Graduations & Prizes and it will be timetabled prior to the examination period. Please check ANU Timetabling for further information.

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

Assignment submission will consist of a Word or PDF (Portable Document Format) report uploaded to Canvas to the relevant Assignment activity through Turnitin. 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.

Hardcopy Submission

There are no hardcopy submissions of assignment in the course.

Late Submission

No submission of assignments without an extension after the due date will be permitted. If an assignment is not submitted by the due date, a mark of 0 will be awarded.

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

Assignment mark and comment will be returned via Canvas or email.

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

No resubmission of assignments is permitted.

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