Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Maggie Lee
Lecturer
Pavel Shevchenko
|
---|---|
Credit points |
Credit points
10
|
Prerequisites |
Prerequisites
(ACST358 or ACST3058) and (ACST359 or ACST3059) and (ACST357 or ACST3057 or ACST3060 or ACST3061)
|
Corequisites |
Corequisites
|
Co-badged status |
Co-badged status
|
Unit description |
Unit description
This unit covers tools and techniques in data analytics. Students will be taught how to apply these skills in a range of business environments and will be able to contribute to all stages of developing solutions to analytical problems across multiple industries or domains. This unit has a focus on practical application using a variety of real-life case studies. Students gaining a grade of credit or higher in this unit are eligible for exemption from the Data Analytics Principles subject of the Actuaries Institute. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Late Assessment Submission Penalty (written assessments)
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical concern.
For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Presentation | 20% | No | Week 8 - See iLearn for details |
Case Studies | 20% | No | Week 12 - See iLearn for details |
Final Exam | 60% | No | University Examination Period |
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 20 hours
Due: Week 8 - See iLearn for details
Weighting: 20%
The presentation is an oral presentation based on a given task. Each student will have 5 minutes for the presentation
Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 20 hours
Due: Week 12 - See iLearn for details
Weighting: 20%
Students will work on two individual case studies.
Assessment Type 1: Examination
Indicative Time on Task 2: 28 hours
Due: University Examination Period
Weighting: 60%
The final examination will be closed book, a three-hour written paper with ten minutes reading time, to be held during the University Examination period.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
Classes
ACST4005 is offered via classes on North Ryde campus (Macquarie University). Students share lecture classes and a common teaching website with the units ACST8095 and ACST7095.
Downloadable lecture recordings
In all weeks, standard recordings of campus lectures using the University's lecture recording facility (ECHO360 or zoom) will be available. The recordings capture audio and screenshot. The recordings will either be provided via the ECHO360 link which is located on the right hand side of the webpage or via a zoom link.
Timetable
The timetable for classes can be accessed through eStudent Class Finder.
Alterations to the class times or locations will be advised in class and on the teaching website.
Teaching staff
Maggie Lee is the unit convenor and will be taking four weeks of classes. Maggie can be contacted via Dialogue on the website, or during her consultation hours.
Professor Pavel Shevchenko will be taking the other weeks of classes. Pavel can be contacted via Dialogue on the website, or during his consultation hours.
We also have a teaching administrator who can deal with any administrative queries related to the unit. They can be contacted via Dialogue on the website (more details to follow).
Assumed knowledge
We assume from the start of the Actuarial Data Analytics that you have acquired the knowledge and skills in subjects from the Foundation Program (Part 1s) of the Actuaries Institute education program.
Lecture slides/Learning Guide
There will be Lecture Slides and/or Learning Guides and associated readings for each section of work. You should read these materials in advance of the lectures, and bring a copy with you to classes.
Technology Used and Required
In this unit, you will need to have access to and to be able to use software to code (R and R studio) and word-processing software to produce reports.
Teaching Website
Course material is available on the online learning management system (iLearn). The teaching website is integral to this unit. Passive involvement in this unit greatly reduces the likelihood of achieving the exemption standard of understanding. Interaction with other students and with teachers is very important, and the website is the forum for that interaction. You will need to be accessing the website regularly to see announcements, read postings and stay informed - at least every couple of days. This is your responsibility and we cannot make any allowances for students who miss important information due to not checking the website regularly. The website entry page is at: http://ilearn.mq.edu.au
Teaching and Learning Activities
The unit is taught as set out in the Classes section. The Unit Schedule sets out the assessment and the topics covered in each week of the session.
Exemptions
The Macquarie University unit ACST4005/ACST7095/ACST8095 will satisfy the requirements for exemption from the Data Analytics Principles subject of the Actuary program of the Actuaries Institute. You will be recommended for exemption if you attain grades of Credit or better in this unit. It is the responsibility of the student to apply to Macquarie University to recommend them to the Actuaries Institute for professional exemptions. More information will be made available via iLearn.
Week |
Week beginning |
Topic |
Lecturer |
Assessment task |
1 |
22-Jul |
Business Environment | ML | |
2 |
29-Jul |
Communication |
ML |
|
3 |
05-Aug |
Data exploration | ML | |
4 |
12-Aug |
Data quality |
ML |
|
5 | 19-Aug | Data manipulation and cleansing | PS | |
6 |
26-Aug |
Basic Concepts and Linear Regression |
PS |
|
7 |
02-Sep | Linear Regression II | PS | |
8 | 9-Sep | Model Selection | PS | Project Presentation |
Break |
16-Sep |
|
|
|
Break |
23-Sep |
|
|
|
9 |
30-Sep |
GLM (Poisson Regression), clustering |
PS | |
10 |
7-Oct |
Regression Tree methods |
PS |
|
11 |
14-Oct |
Classification |
PS |
|
12 |
21-Oct |
Neural Networks and Generalised Additive Models |
PS |
Case Studies |
13 |
28-Oct |
Mortality modelling using regression tree |
PS |
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via the Service Connect Portal, or contact Service Connect.
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Unit information based on version 2024.01R of the Handbook