Course Catalog
AWS Discovery Day: Machine Learning Basics
Code: AWS Discovery Day
Duration: 1 Session
$0 USD

OVERVIEW

Are you interested in machine learning, but not sure where to start? Join us for this session with an AWS expert and demystify the basics. Using real-world examples, you’ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can unlock new insights and value for your business using machine learning.

  • Level: Fundamental
  • Duration: 1.5 hours
DELIVERY FORMAT

This course is available in the following formats:

Virtual Classroom

Duration: 1 Session

CLASS SCHEDULE

Delivery Format: Virtual Classroom
Date: Apr 05 2024 - Apr 05 2024 | 11:30 - 13:00 EDT
Location: Online
Course Length: 1 Session

$ 0

Delivery Format: Virtual Classroom
Date: Jul 12 2024 - Jul 12 2024 | 11:30 - 13:00 EDT
Location: Online
Course Length: 1 Session

$ 0

GOALS

During this event, you will learn:

  • What is Machine Learning?
  • What is the machine learning pipeline, and what are its phases?
  • What is the difference between supervised and unsupervised learning?
  • What is reinforcement learning?
  • What is deep learning?
OUTLINE

Will Be Updated Soon!

Section 1: Machine learning basics

  • Classical programming vs. machine learning approach
  • What is a model?
  • Algorithm features, weights, and outputs
  • Machine learning algorithm categories
  • Supervised algorithms
  • Unsupervised algorithms
  • Reinforcement learning

Section 2: What is deep learning?

  • How does deep learning work?
  • How deep learning is different

Section 3: The Machine Learning Pipeline

  • Overview
  • Business problem
  • Data collection and integration
  • Data processing and visualization
  • Feature engineering
  • Model training and tuning
  • Model evaluation
  • Model deployment

Section 4: What are my next steps?

  • Resources to continue learning
LABS

Will Be Updated Soon!
Will Be Updated Soon!
WHO SHOULD ATTEND

This event is intended for:

  • Developers
  • Solution architects
  • Data engineers
  • Individuals interested in building solutions with machine learning - no machine learning experience required!
PREREQUISITES

None