Machine Learning for Business

• Articulate why machine learning techniques have been able to disrupt numerous industries.
• Describe the fundamental phases of a machine learning project.
• Recall the historical development of machine learning technology.
• List example problems that machine learning can solve.
• Distinguish between regression and classification problems.
• Distinguish between supervised and unsupervised machine learning.
• Identify aspects of your work that can benefit from machine learning.
• Organise a machine learning project using an AI canvas.
• List the stakeholders that are involved in the execution of a machine learning project.
• Formulate data governance processes which establish the necessary foundations for a machine learning project.
• Differentiate between various data types.
• Assess the performance of a machine learning solution.

This program is particularly suited for leaders and managers who want to understand what machine learning is, and how it could apply to your business. 

The program is not suitable for technical experts.

In this practical workshop, you will gain a working knowledge of machine learning and how it could apply to your business. You will learn what machine learning is, what data is required that will equip you with the relevant knowledge to discover opportunities and drive efficiency in your business.

Your organisation will gain an individual with an understanding of artificial intelligence and machine learning and how it being applied to business and if it could be applied to your business and context.

• You will receive a soft copy University of Adelaide Certificate of Completion.
• This PACE course may contribute to earning Continuing Professional Development (CPD) points or credit. Many professional associations accredit CPD at a standard rate of 1 hour of professional development / learning = 1 CPD point. This should be used as a guide only and confirmation should be sought from your accrediting body prior to registration in any PACE course or program.