OOP Programming with Gen AI Co Pilot

Unit code: NIT2004 | Study level: Undergraduate
Credit points
12
(Generally, 1 credit = 10 hours of classes and independent study.)
Location
Footscray Park
Online Real Time
VU Brisbane
VU Sydney
Prerequisites
NIT1102 - Introduction to Programming
(Or equivalent to be determined by unit coordinator)
Overview
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Overview

In this unit, you will learn Object-Oriented Programming (OOP) using Python, focusing on core principles such as encapsulation, inheritance, polymorphism, and modular design. You will use AI-assisted coding tools like GenAI Copilot to automate code generation, optimisation, and debugging. You are expected to apply best practices in software development, including design patterns, structured programming, and error handling, to build scalable, maintainable applications. Through hands-on projects, collaborative coding, and real-world case studies, you will develop well-structured, functional software and integrate AI-powered enhancements where appropriate. By the end of the unit, you can confidently contribute to software development in AI-augmented environments.

Learning Outcomes

On successful completion of this unit, students will be able to:

  1. Analyse core Object-Oriented Programming principles to distinguish their roles in modular software design;
  2. Integrate AI tools into the OOP development workflow to support code generation, debugging, and documentation;
  3. Design modular software solutions using OOP principles and AI copilots;
  4. Analyse and optimise OOP systems using AI copilots, focusing on exception handling, performance, and maintainability;
  5. Present technical designs, functionality, trade-offs, and the role of AI in software development.

Assessment

For Melbourne campuses

Assessment type: Test
|
Grade: 20%
Online theory test
Assessment type: Test
|
Grade: 30%
Practical test with verified live interaction.
Assessment type: Assignment
|
Grade: 50%
Project (OOP system using OOP and AI) with demonstration, presentation and oral Q&A.

Test: Supervised hands-on coding or data handling task. Students are required to explain steps and decisions through written justifications or post-test oral reviews to verify authenticity.

Assignment: Includes structured milestone reviews and in-class progress checks. Individual contributions are logged, validated, and justified through recorded peer review or demonstration to ensure authenticity. Students need also present technical insights or project findings in real-time, followed by a Q&A session. Understanding is verified via unpredictable questions requiring explanation of methods, assumptions, and decisions.

Required reading

Selected readings are provided on VU Collaborate.

As part of a course

This unit is studied as part of the following course(s):

Bachelor of Data Science
NBDS | Bachelor degree | Duration: 3 years

Refer to the course page for information on how to apply for the course. VU takes care to ensure the accuracy of this unit information, but reserves the right to change or withdraw courses offered at any time. Please check that unit information is current with the Student Contact Centre.

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