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BUSN12003 - Artificial Intelligence for Business

General Information

Unit Synopsis

In this exciting journey, you'll dive into the captivating realm of Artificial Intelligence, gaining theoretical insights and applying practical knowledge with cutting-edge skills. Unleash your curiosity as you explore the dynamic interplay between Artificial Intelligence, Machine Learning, and Deep Learning, unravelling their unique applications in the business landscape. Brace yourself for a mind-bending exploration of Generative AI, coupled with the essential artistry of Prompt Engineering. This unit is your ticket to not just understanding but actively shaping the future of Artificial Intelligence and its tech companions to meet the ever-evolving demands of the business world. While studying the unit you will learn how Artificial Intelligence can help various industries such as healthcare, mining, agriculture, education, supply chain to solve their problems or take advantage of this emerging technology to transform their business. Furthermore, this unit will also introduce the social and ethical considerations of using AI for business.

Details

Level Undergraduate
Unit Level 2
Credit Points 6
Student Contribution Band SCA Band 4
Fraction of Full-Time Student Load 0.125
Pre-requisites or Co-requisites There are no pre-requisites for the unit.

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Class Timetable View Unit Timetable
Residential School No Residential School

Unit Availabilities from Term 3 - 2024

Term 1 - 2025 Profile
Online

Attendance Requirements

All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Assessment Overview

Recommended Student Time Commitment

Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Assessment Tasks

Assessment Task Weighting
1. Case Study 20%
2. Practical Assessment 50%
3. Presentation 30%

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%).

Consult the University's Grades and Results Policy for more details of interim results and final grades

Past Exams

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Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Unit learning Outcomes

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

  1. Explain key concepts of Artificial Intelligence, Machine Learning, and Deep Learning and their use in businesses including social innovation
  2. Apply Artificial Intelligence such as algorithms and neural networks to solve business problems
  3. Explain social and ethical considerations of Artificial Intelligence

Alignment with SFIA (Skills Framework for the Information Age)
SFIA is a skills framework widely adapted by public and private institutions around the world. It defines the skills and competencies required by business and technology professionals working in digital technologies and/or solutions that involves a mix of technical and non-technical skills.

This unit encompasses the following five workplace skillsets as defined by SFIA 8:

  1. Requirements definition and management (REQM)
  2. Business modelling (BSMO)
  3. Business intelligence (BINT)
  4. Programming/software development (PROG)
  5. Research (RSCH)
     

Alignment of Assessment Tasks to Learning Outcomes
Assessment Tasks Learning Outcomes
1 2 3
1 - Case Study •
2 - Practical Assessment •
3 - Presentation •
Alignment of Graduate Attributes to Learning Outcomes
• Introductory Level
• Intermediate Level
• Graduate Level
Graduate Attributes Learning Outcomes
1 2 3
1 - Communication • •
2 - Problem Solving • •
4 - Information Literacy • • •
5 - Team Work •
6 - Information Technology Competence • •
7 - Cross Cultural Competence •
8 - Ethical practice •
9 - Social Innovation •
Alignment of Assessment Tasks to Graduate Attributes
• Introductory Level
• Intermediate Level
• Graduate Level
Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8 9 10