ENG1142 · AI for business and healthcare

Overview

In this unit, we explore the transformative power of Artificial Intelligence (AI) across the healthcare and business landscapes, combining foundational knowledge with practical applications. In healthcare, you will learn how AI is revolutionising patient care, from disease diagnosis to public health management. We will cover AI techniques for predictive modelling, clinical decision-making, patient monitoring and precision medicine while focusing on ethical challenges such as patient privacy, algorithmic bias and health equity. This ensures your approach to AI in healthcare is responsible, safe and in line with industry standards. In the business and commerce sectors, you will develop a strategic perspective on using AI to tackle real-world challenges in marketing, finance, management and more. You will explore how to apply AI to gain insights into customer behaviour and improve data-driven decision-making. Additionally, you will gain hands-on experience with AI tools that enhance operational efficiency, drive digital transformation and promote ethical data governance. By examining AI in healthcare and business, this unit equips you to drive innovation, adapt to rapidly evolving industries and make impactful, ethical decisions with AI.

Offerings

The Handbook publishes no offerings for this unit.

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Continuous assessment: 100%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Demonstrate knowledge of the foundational principles of Artificial Intelligence (AI), Machine Learning (ML) and data analysis by identifying their applications and assessing their impact in healthcare and business contexts.
2. Apply AI concepts to improve decision-making, efficiency and problem-solving by designing practical implementation strategies in healthcare and business.
3. Evaluate ethical, equity, privacy and safety considerations for responsible and fair AI use in diverse real-world scenarios.
4. Interpret AI model outputs for accuracy, reliability and contextual relevance to support informed decision-making in healthcare and business.
5. Analyse the real-world challenges in AI adoption and identify solutions to address these barriers effectively.
6. Apply large language models, natural language processing and prompt engineering techniques to optimise text-based and analytical tasks in healthcare and business.

Workload

The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.

Student experience, not official rules. Nothing here changes what the Handbook says.