MIT9317 Data Science Capstone

Unit Code

MIT9317

Level

Postgraduate

Campus

Sydney

Prerequisites

MIT9301 and 100 credit pts of which 80 credit pts mustbe at level 8000

Credit Points

Subject Description

In the MIT9317 Data Science Capstone Project, students apply the knowledge and skills acquired throughout their Master of Information Technology (Data Science) degree. Typically working in groups of 3 to 5 students, they undertake an industry-relevant data science project for a client. The project involves addressing a complex, real-world data-driven problem, encompassing the entire process from project planning, problem definition, data collection, data preprocessing, exploratory data analysis, model development, and evaluation to deployment, ensuring adherence to ethical and responsible AI standards. The subject includes regular progress reports, project documentation, results presentation, and final evaluation. Students are expected to demonstrate proficiency in applying various data science methodologies, including statistical analysis, machine learning, predictive modeling, and data visualisation, to provide actionable insights and effective solutions to the client’s problem.

Course

Master of Information Technology (Data Science)

Course Level

Level 2

Subject Type

☒ Capstone

Study Mode: Face to face on site

Study Load: Full-time

Learning Topics

Client-focused data science project planning and requirements analysis
Data collection and exploratory analysis
Statistical analysis, machine learning and predictive modelling
Model evaluation and actionable insights
Ethical and responsible AI, teamwork and stakeholder communication

Subject Learning Outcomes

Apply theoretical, professional and technical knowledge and skills to achieve project deliverables.
Elicit, analyse, and critically refine organisational IT requirements to develop a well-informed approach for a secure data science solution.
Design and implement an advanced data science methodology to deliver a comprehensive solution with a focus on ethical considerations.
Critically assess the quality and effectiveness of all aspects of the developed solution, through evaluation of project processes and supporting documentation.
Collaborate and communicate effectively with team members as well as external stakeholders ensuring compliance with ethical, legal, professional and industry standards.

Assessment

AIIHE uses a variety of assessment tools to guide and assess each student’s achievement of the subject learning outcomes. In this capstone subject, students develop a group charter and team plan, provide regular project-progress reports, and complete a final project comprising a group report and deliverables, a presentation and an individual reflection. These tasks assess project planning, applied technical capability, critical evaluation, collaboration, stakeholder communication and professional practice.

Summary of Assessment

Assessment Type	Due Date	Weighting
Assessment 1: Group Charter and Team Plan	Week 4	15%
Assessment 2: Project Progress	Weeks 2, 4, 6, 8 and 10	10%
Assessment 3: Final Project Report	Weeks 11 and 12	70%

Learning Resources

AIIHE will update the topic coverage of the subject and the available relevant learning resources at the time of subject delivery. In the interim, AIIHE provides the following indicative list of relevant reference material. AIIHE also subscribes to eLearning Resources through the Canvas portal, and where relevant material is available, AIIHE will seek to source reference material from this system for staff and student access.