Programming Language and Pseudocode

Unit code:NIT5001Study level:Postgraduate

Credit points

12
(Generally, 1 credit = 10 hours of classes and independent study.)

Location

City Campus
Online Real Time
VU Brisbane
VU Sydney

Prerequisites

(Or equivalent to be determined by unit coordinator)
Co-requisites
(Corequisite units must be studied concurrently with this unit)

Overview

In this unit, you will develop the core skills needed to turn real-world problems into clear, implementable software solutions. You will explore how programming languages operate within computer systems and learn how to choose an appropriate language for a given scenario. You will practise designing algorithms using pseudocode as a platform-agnostic method to express logic, structure solutions, and communicate design decisions before implementation.

You will apply problem decomposition, abstraction, and stepwise refinement to create and evaluate algorithm designs for practical tasks. Using contemporary AI tools and large language models (LLMs), you will learn how to draft and improve pseudocode, generate code in specified programming languages, and support debugging, testing, and documentation. You will also develop the critical judgement needed to verify AI-generated outputs, identify errors or limitations, and justify your final solutions in line with academic integrity and professional practice.

By the end of the unit, you will be able to design robust algorithmic solutions, present them effectively using pseudocode, and implement them as working programs using AI-supported development workflows

Learning Outcomes

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

Critically analyse how programming languages interact with computer systems including execution models, data representation and other possible modules, to inform solution design choices.
Design and justify algorithmic solutions to real-world problems using clear, structured pseudocode and appropriate abstraction.
Evaluate and select suitable programming languages and development approaches for a given scenario, considering constraints, stakeholders and quality attributes.
Implement and refine working programs from pseudocode designs, applying systematic testing and debugging to improve correctness and robustness.
Critically evaluate and responsibly apply AI tools/LLMs to support pseudocode development and code generation, including verification of outputs and adherence to integrity and professional standards.