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Introduction to Machine Learning: Art of the Possible

This digital course is designed to help business decision-makers understand the fundamentals of machine learning (ML).

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

About Instructor

AWS

110 Courses

Not Enrolled
FREE

Course Includes

  • 1 Lesson
  • Instructor: AWS

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