Overview

The purpose of this unit is to develop students' digital capability with AI by introducing key concepts of artificial intelligence, logic flow and process mapping, and prompt engineering, with a focus on applications in health and wellbeing contexts.

Requisites

Prerequisites
COS10022 Data Science Principles
Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 2
Location
Hawthorn
Start and end dates
02-August-2027
31-October-2027
Last self-enrolment date
15-August-2027
Census date
31-August-2027
Last withdraw without fail date
21-September-2027
Results released date
07-December-2027

Unit learning outcomes

Students who successfully complete this unit will be able to:

  1. Apply problem-solving techniques using logic-flow design and AI-powered prototyping.
  2. Explain artificial intelligence concepts and evaluate the practical applications in health and wellbeing contexts.
  3. Apply basic principles, models and prototyping techniques in artificial intelligence to solve problems in health and wellbeing contexts.
  4. Analyse real-world wellbeing problems and justify the selection of appropriate artificial intelligence approaches.
  5. Evaluate the ethical, societal and health equity implications of artificial intelligence, including digital bias.

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)

On-Campus

Class 

 2 12 weeks 24

Online

Lecture (asynchronous)

 1 12 weeks 12

Specified Activities

Various

 3 12 weeks 60

Unspecified Activities 

Independent Learning

 4.5 12 weeks 54
Total     150

Assessment

Type Task Weighting ULOs
Project Individual/Group 40% 1,2,3,4,5
Activity Report Individual 40% 3,4,5
Test 1 Individual 20% 1,2

Content

  • Introduction to AI Concepts,
  • Logic Flows and Computational Thinking;
  • Human-Centred Problem Solving for Health and Wellbeing;
  • Workflow Analysis, Process Mapping and Opportunity Identification;
  • Prompt Engineering and Human–AI Collaboration;
  • AI-Driven Prototyping and Evaluation for Rapid Solution Development;
  • Applications of AI and Digital Health Across Health and Care Settings;
  • Benefits, Risks, Ethics and Responsible AI Prototyping.
  • Graduate Attribute 1 - Communication 1- Verbal Communication
  • Graduate Attribute 2 - Communication 2 - Communicating using different media
  • Graduate Attribute 3 - Teamwork 1 - Collaboration and negotiation
  • Graduate Attribute 4 - Teamwork 2 - Teamwork roles and processes
  • Graduate Attribute 5 - Digital Literacies 1 -Information literacy
  • Graduate Attribute 6 - Digital Literacies 2 - Technical literacy

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.