Course Title: Cloud-Enabled AI and Analytics for Business

Part A: Course Overview

Course Title: Cloud-Enabled AI and Analytics for Business

Credit Points: 12.00


Course Coordinator: Su Nguyen

Course Coordinator Phone: +61 3 9925

Course Coordinator Email: Su.Nguyen@rmit.edu.au

Course Coordinator Location: Melbourne City Campus

Course Coordinator Availability: Appointment via email


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed knowledge: BUSM2723 Cloud Solutions for Enterprises.


Course Description

This course considers new and emerging AI and analytics applications powered by cloud computing platforms. You will learn basic concepts in the use of AI and analytics technologies, and how these can be used to achieve sustainable operational efficiencies in business, in light of the United Nations Sustainable Development Goal for building resilient infrastructure and promoting sustainable industry and innovation (SDG9).

The course provides an understanding of key concepts and core components of AI and analytics products and their applications in business. It describes the typical life-cycle of AI and analytics projects. It introduces design patterns for common AI and analytics solutions for business, and the use of generative artificial intelligence, self-serve analytics, and AI Copilot. The course also provides an understanding of risks associated with AI and Analytics products when deployed in cloud environments.


Objectives/Learning Outcomes/Capability Development

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You will achieve the following course learning outcomes (CLOs) upon successful completion of this course:

CLO1: Evaluate and discuss new and emerging AI and analytics applications.

CLO2: Critically review AI and analytics technologies, and how they can be used to achieve operational efficiencies in business.

CLO3: Contextualise how the core components of AI and analytics products apply in a business context.

CLO4: Evaluate the risks and ethical concerns associated with AI and Analytics products.

CLO5: Recommend design patterns for common AI and analytics solutions for business and analyse the typical life-cycle of AI and analytics projects.


Overview of Learning Activities

This course uses highly structured learning activities to guide your learning process and prepare you for the assessments. The activities are a combination of individual, peer-supported and facilitator-guided activities, and where possible project-led, with opportunities for feedback throughout.

The learning activities have been designed to assist you in the development of a number of important graduate capabilities. Authentic and industry-relevant learning is central to this course, and you will be encouraged to critically compare and contrast important considerations in the implementation of cloud technologies for business, informed by your personal insights.

You are expected to consistently apply yourself to the course throughout the semester. Social learning is another important component, and you are expected to participate in class and group activities, share drafts of work and resources and give and receive peer feedback. You will be expected to work efficiently and effectively with others to achieve outcomes greater than those that you might have achieved alone.

Seminars/workshops are designed to supplement the material provided on the RMIT CANVAS site and the recommended readings. Discussions in seminars are specifically designed using group work and problem-solving activities so that you may critical analyse topics covered throughout the semester. The seminar setting also provides the opportunity for you to critically evaluate problems and develop confidence in your ability to apply theoretical issues to practical situations.


Overview of Learning Resources

A range of recordings, texts and articles will be referred to in class. You will be given a list of suggested readings and audio- visual recordings, but you are required to undertake further research throughout the duration of the course. Feedback will be provided throughout the semester in class and/or in online discussion forums through individual and group feedback on practical exercises and individual consultation.

RMIT Library provides extensive resources, services and study spaces. All RMIT students have access to scholarly resources including course related material, books, e-books, journals and databases.

Computers and printers are available at every Library. You can access the Internet and Library e-resources. You can also access the RMIT University wireless network in the Library.

Contact: Ask the Library for assistance and information on Library resources and services: http://www.rmit.edu.au/library. Study support is available for assistance with assignment preparation, academic writing, information literacy, referencing, maths and study skills. Additional resources and/or sources to assist your learning will be identified by your course coordinator and will be made available to you as required during the teaching period.


Overview of Assessment

The assessment alignment list below shows the assessment tasks against the learning outcomes (CLOs).

Assessment Task 1: 25%

Linked CLOs 1, 3, 4

Assessment Task 2: 35%

Linked to CLOs 1, 2, 4, 5

Assessment Task 3: 40%

Linked to CLOs 1, 3, 4, 5