AWS Academy Machine Learning Foundations introduces students to the concepts and terminology of Artificial Intelligence and machine learning. By the end of this course, students will be able to select and apply machine learning services to resolve business problems. They will also be able to label, build, train, and deploy a custom machine learning model through a guided, hands-on approach.
Upon completion of this course, students will be able to:
Describe machine learning (ML)
Implement a machine learning pipeline using Amazon SageMaker
Use managed Amazon ML services for forecasting
Use managed Amazon ML services for computer vision
Use managed Amazon ML services for natural language processing
Student Prerequisites
To ensure success in this course, students should have the following:
Completed AWS Academy Cloud Foundations (or another introductory cloud computing course)
Experience scripting with Python or equivalent
A basic understanding of statistics
Intended Audience
This introductory course is intended for students interested in pursuing a career in data science, ML, and AI.
Module Outline
MODULE 1 | Welcome to AWS Academy Machine Learning Foundations
MODULE 2 | Introducing Machine Learning
MODULE 3 | Implementing a Machine Learning pipeline with Amazon SageMaker
MODULE 4 | Introducing Forecasting
MODULE 5 | Introducing Computer Vision
MODULE 6 | Introducing Natural Language Processing
NEED MORE INFORMATION ABOUT THIS COURSE?
Complete the fields below to receive the course information pack. *Required fields
By providing us with your contact details, you agree to the use of your data as described in our terms and conditions to receive communications. You may opt out of receiving communications at any time.
