Introduction to Machine Learning: Art of the Possible

Description

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 in 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 markets

Module 2: How does machine learning work?
•Describe artificial intelligence
•Describe the difference between artificial intelligence and machine learning

Module 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 models

Module 4: Conclusion