AWS Academy Machine Learning Foundations

This course introduces students to the concepts and terminology of Artificial Intelligence (AI), machine learning, and generative AI. 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.

FAQs

Question: Does this course prepare students for an AWS certification?

Answer: Amazon Web Services has recently updated their certification paths with several new credentials in Machine Learning and Data Science. This introductory course will build the foundation students will need to prepare for these new exams and provide the skills needed to enter this growing field.

Course Objectives

• 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 
• Identify how Amazon ML services for generative AI are used 

Prerequisites

• Completed an introductory cloud computing course.
• Experience scripting with Python or equivalent 
• A basic understanding of statistics 

Curriculum

• Subject 1 – Introduction to AWS Academy Machine Learning Foundations 
• Subject 2 – Introduction to Machine Learning 
• Subject 3 – Implementing a Machine Learning pipeline with Amazon SageMaker 
• Subject 4 – Introduction to Forecasting 
• Subject 5 – Introduction to Computer Vision (CV) 
• Subject 6 – Introduction to Natural Language Processing 
• Subject 7 – Introduction to Generative AI 
• Subject 8 – Course Wrap-Up