Planning a Machine Learning Project

Lay the groundwork for successful machine learning projects

Explore how successful machine learning projects begin by evaluating business challenges, assessing organisational readiness, and determining when machine learning is the right approach to achieve meaningful outcomes.

Turn business requirements into machine learning strategies

Discover how to identify suitable machine learning use cases, assess data readiness, consider project timelines, and plan for successful deployment, helping you make informed decisions throughout the machine learning project lifecycle.

Please note that to access the course content for this AWS course, you will go via an LTI link(s) to the AWS platform; you can then return to the FutureLearn course and mark the step as complete in order to receive your certificate.

This course is ideal for non-technical business leaders and decision-makers who are involved in, or preparing to support, machine learning projects. It is also suitable for participants of the AWS Machine Learning Embark program and Machine Learning Solutions Lab (MLSL) discovery workshops.

This course is ideal for non-technical business leaders and decision-makers who are involved in, or preparing to support, machine learning projects. It is also suitable for participants of the AWS Machine Learning Embark program and Machine Learning Solutions Lab (MLSL) discovery workshops.

• Describe how to determine if machine learning is the right solution to your business problem
• Describe the process of ensuring if your business data is machine learning ready
• Explain the impacts machine learning has to a project timeline
• Ask questions that affect machine learning model deployment to production