Managing Machine Learning projects with Google Cloud

• Thoroughly understand how ML can be used to improve business processes and create new value
• Explore common machine learning use cases implemented by businesses
• Identify the requirements to carry out an ML project, from assessing feasibility to data preparation, model training, evaluation, and deployment
• Define data characteristics and biases that affect the quality of ML models
• Recognize key considerations for managing ML projects, including data strategy, governance, and project teams
• Pitch a custom ML use case that can meaningfully impact your business