Machine Learning for Executives
Ended Jun 19, 2020
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Full course description
OverviewMachine Learning is disrupting industry. From financial services to medical devices to legal services, machine learning technology is changing the way businesses operate.
Aimed at executives and professionals wanting to understand machine learning and its applications, this course will take you through the fundamental stages of a machine learning project, from conceptualisation to development to evaluation.
Seeing the evolution of a complete machine learning project will give you a unique perspective, allowing you to engage with key concepts, and understand where machine learning could apply in your organisation.
The course will equip you with the knowledge you need to prepare your organisation for machine learning technology.
What will you learn?
- 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
Who is this for?
The program is not suitable for technical experts.
Dr Zygmunt Szpak - Australian Institute for Machine Learning
Zygmunt received his PhD degree in Computer Science from the University of Adelaide, Australia in 2013, and his MSc degree in Computer Science from the University of KwaZulu-Natal, South Africa in 2009. He is a senior research fellow at the Australian Institute for Machine Learning. His research lies at the interface of computer vision, machine learning, and challenging industry problems. He develops algorithms that allow computers to perform tasks typically associated with human intelligence. In the last couple of years, his work has focused on the application of machine learning and image processing techniques for the development of smart medical devices. His responsibilities at the institute include teaching industry and partner organisations how to transform their business with machine learning technology.