Managing Machine Learning Projects with Google Cloud
Managing Machine Learning Projects with Google Cloud
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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.
Course Info
Objectives
- Explore common machine learning use cases implemented by businesses.
- Assess the feasibility of your own ML use case and its ability to meaningfully impact your business.
- Identify the requirements to build, train, and evaluate an ML model.
- Define data characteristics and biases that affect the quality of ML models.
- Recognize key considerations for managing ML projects.
Prerequisites
• No prior technical knowledge is required.
• Savvy about your own business and objectives.
• Recommended: Business Transformation with Google Cloud (on-demand).
Audience
Enterprise, corporate, or SMB business professionals in non-technical roles. Roles include but are not limited to: business analysts, IT managers, project managers, and product managers.
For senior VPs and above, Data-Driven Transformation with Google Cloud (ILT) is more suitable.
Available languages
English
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