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ENAI11-100: Computational Thinking

Description

Computational Thinking is a foundation subject that introduces students to problem-solving used in modern computing and AI environments. Topics include decomposition, recognising patterns, abstracting structures and logic flows, and developing algorithms that are generalisable and reusable. Other important skills covered are debugging and testing.  Students will learn to apply these concepts both in theory and practice, building skills that are used to tackle real-world problems. The traditional computational methods are blended with emerging AI. Students will learn how to integrate AI tools into a workflow to produce, optimise and validate code used in business environments

Subject details

Type: Undergraduate Subject
Code: ENAI11-100
EFTSL: 0.125
Faculty: Bond Business School
Credit: 10
Study areas:
  • Business, Commerce, and Entrepreneurship
Subject fees:
  • Commencing in 2026: $4,600.00
  • Commencing in 2026: $6,260.00

Learning outcomes

  1. Explain how core principles of computational thinking including decomposition, pattern recognition, and abstraction can be used to solve structured and semi-structured problems.
  2. Design algorithmic solutions in an appropriate programming language using fundamental algorithmic principles and concepts.
  3. Apply AI tools to assist in code generation, debugging, and documentation of projects designed to address common business problems.
  4. Evaluate the benefits, limitations, and ethical considerations relevant to assessing the responsible use of AI.
  5. Communicate computational solutions to technical and non-technical audiences using appropriate abstractions, diagrams, and code.

Enrolment requirements

Requisites:

Nil

Restrictions:

Nil