This course introduces requirements to determine if machine learning (ML) is the appropriate solution to a business problem. • Course level: Fundamental • Duration: 30 minutes Activities: This course includes presentations, videos, and knowledge assessments. Course objectives: In this course, you will learn to: • Identify the data, time, and production requirements for a successful ML project Intended audience: This course is intended for: • Nontechnical business leaders and other business decision makers who are, or will be, involved in ML projects • Participants of the AWS Machine Learning Embark program, and Machine Learning Solutions Lab (MLSL) discovery workshops Prerequisites: We recommend that attendees of this course have: • Introduction to Machine Learning: Art of the Possible Course outline: Module 1: Is a machine learning solution appropriate for my problem? • Explain how to determine if ML is the appropriate solution to your business problem Module 2: Is my data ready for machine learning? • Describe the process of ensuring that your data is ML ready Module 3: How will machine learning impact a project timeline? • Explain how ML can impact a project timeline Module 4: What early questions should I ask in deployment? • Identify the questions to ask that affect ML deploymentModule 5: Conclusion
