This digital course is designed to help business decision makers understand the fundamentals of machine learning (ML).
• Course level: Fundamental
• Duration: 30 minutes
Activities
This course includes presentations, videos, and knowledge assessments.
Course objectives
In this course, you will learn to: • Understand the basics of machine learning to help evaluate the benefits and risks associated with adopting ML in various business cases
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: • Basic knowledge of computers and computer systems • Some basic knowledge of the concept of machine learning
Course outline
Module 1: How can machine learning help? • Define artificial intelligence • Define machine learning • Describe the different business domains impacted by machine learning • Describe the positive feedback loop (flywheel) that drives ML projects • Describe the potential for machine learning in underutilized marketsModule 2: How does machine learning work? • Describe artificial intelligence • Describe the difference between artificial intelligence and machine learningModule 3: What are some potential problems with machine learning? • Describe the differences between simple and complex models • Understand unexplainability and uncertainty problems with machine learning modelsModule 4: Conclusion
Course Instructor
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