Students
AFIN2070 – Financial Data Analytics
2025 – Session 2, In person-scheduled-weekday, North Ryde
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Hieu Nguyen
|
|---|---|
| Credit points |
Credit points
10
|
| Prerequisites |
Prerequisites
AFIN1002 and (STAT1250 or STAT1170 or STAT1371)
|
| Corequisites |
Corequisites
|
| Co-badged status |
Co-badged status
|
| Unit description |
Unit description
This unit introduces students to the fundamental process of data analytics in finance. It focuses on developing critical computational, statistical, and other contemporary analytical skills that are essential for people conducting data-driven financial analytics. With an emphasis on applied learning informed by a strong theoretical foundation, the lectures use real-data examples to discuss contemporary topics such as data management and visualisation, financial risk analysis and prediction, regression and classification methods, and clustering. Students will practice their learned concepts and analytical skills through applied data-driven case studies using computer software tools and industry-standard financial databases. |
Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- ULO1: Critically examine core predictive and classification methods in financial data analytics
- ULO2: Evaluate and apply data analytics skills using computer software tools to solve real-world problems in the finance industry.
- ULO3: Apply working knowledge of data analytics to extract and report insights from financial data in various forms.
General Assessment Information
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.
Assessment Tasks
| Name | Weighting | Hurdle | Due |
|---|---|---|---|
| Professional Practice: Industry database training | 30% | No | Week 6 |
| Formal and Observed Learning: Test | 30% | No | Week 8 |
| Professional Practice: Applied data analysis | 40% | No | Week 13 |
Professional Practice: Industry database training
Assessment Type 1: Practice-based task
Indicative Time on Task 2: 20 hours
Due: Week 6
Weighting: 30%
The purpose of this assessment is to enable you to develop expertise in utilizing and applying quantitative analysis techniques to industry databases.
You will complete a training module provided by a financial database provider. In addition, you will extract data from the financial database and perform data analysis tasks to solve financial problems.
Skills in focus:
- Critical thinking and problem solving
- Digital skills
- Work readiness
Deliverable: Complete financial database certification and submit an Excel spreadsheet. Individual assessment
On successful completion you will be able to:
- Critically examine core predictive and classification methods in financial data analytics
- Evaluate and apply data analytics skills using computer software tools to solve real-world problems in the finance industry.
Formal and Observed Learning: Test
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 15 hours
Due: Week 8
Weighting: 30%
The purpose of this assessment is for you to demonstrate your understanding and knowledge of key topics from the unit.
You will participate in a formal test. Feedback on your performance will help you assess your progress through the unit content.
Deliverable: Test Individual assessment
On successful completion you will be able to:
- Critically examine core predictive and classification methods in financial data analytics
- Evaluate and apply data analytics skills using computer software tools to solve real-world problems in the finance industry.
- Apply working knowledge of data analytics to extract and report insights from financial data in various forms.
Professional Practice: Applied data analysis
Assessment Type 1: Project
Indicative Time on Task 2: 35 hours
Due: Week 13
Weighting: 40%
The purpose of this assessment is for you to demonstrate the expertise they have acquired in the unit by analysing real-world financial data.
You will conduct financial data analytics tasks and provide insights based on the information obtained.
Skills in focus:
- Critical thinking and problem solving
- Communication
- Digital skills
- Work readiness
Deliverable: Python code and Excel submission Individual assessment
On successful completion you will be able to:
- Critically examine core predictive and classification methods in financial data analytics
- Evaluate and apply data analytics skills using computer software tools to solve real-world problems in the finance industry.
- Apply working knowledge of data analytics to extract and report insights from financial data in various forms.
1 If you need help with your assignment, please contact:
- the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
- the Writing Centre for academic skills support.
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
Delivery and Resources
Please find the details of delivery and resources in iLearn.
Policies and Procedures
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:
- Academic Appeals Policy
- Academic Integrity Policy
- Academic Progression Policy
- Assessment Policy
- Fitness to Practice Procedure
- Assessment Procedure
- Complaints Resolution Procedure for Students and Members of the Public
- Special Consideration Policy
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.
Student Code of Conduct
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
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
Academic Integrity
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.
Student Support
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- Workshops
- Chat with a WriteWISE peer writing leader
- Access StudyWISE
- Upload an assignment to Studiosity
- Complete the Academic Integrity Module
The Library provides online and face to face support to help you find and use relevant information resources.
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- IT Support
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Student Enquiries
Got a question? Ask us via the Service Connect Portal, or contact Service Connect.
IT Help
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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 2025.06 of the Handbook