Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Find out how you can discover unexpected use cases, recognize the phases of an ML project and considerations within each, and gain confidence to propose a custom ML use case to your team or leadership or translate the requirements to a technical team.
Overview
Business professionals in non-technical roles have a unique opportunity to lead or influence machine learning projects. If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Find out how you can discover unexpected use cases, recognize the phases of an ML project and considerations within each, and gain confidence to propose a custom ML use case to your team or leadership or translate the requirements to a technical team.
Syllabus
- Introduction 5mins
- Identifying business value for using ML 25mins
- Defining ML as a practice 42mins
- Building and evaluating ML models 55mins
- Using ML responsibly and ethically 31mins
- Discovering ML use cases in day-to-day business 44mins
- Managing ML projects successfully 48mins
- Summary 8mins
- Course Resources 0mins
Taught by
Google Cloud
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