Machine Learning University

Self-service machine learning training from Amazon's own scientists

Machine Learning University (MLU) provides anybody, anywhere, at any time access to the same machine learning courses used to train Amazon’s own developers on machine learning. With MLU, all developers can learn how to use machine learning with the learn-at-your-own-pace MLU Accelerator learning series. The MLU Accelerator series is designed to kick-start your ML journey with three, three-day foundational courses on Natural Language Processing, Tabular Data, and Computer Vision. Upon completion of the Accelerator Series, the Decision Trees and Ensemble Methods course offers a more advanced, five-day lecture series on tree-based and ensemble models. Through sequential YouTube videos taught by Amazon scientists with hands-on practical examples, Jupyter notebooks, and slide decks, MLU provides a comprehensive self-service pathway to understanding the foundations of machine learning. Course materials are available on GitHub, see below for more details about our courses.

MLU Channel Introduction

Get Started

The courses offered from Machine Learning University are the same courses used to train Amazon's own developers on machine learning fundamentals. Getting started with MLU is easy and provides learners with a self-paced and flexible learning structure.

Brush-up on basics

To get started with MLU, all users must create an AWS account. It is also recommended that learners have a basic understanding and familiarity with Python to make the most of this content. If you're not familiar with Python, check out some of our other learning resources for introductory tutorials. 

Choose a learning path

Choose one of three learning paths based on your needs. Each learning path includes lectures on YouTube, slides, hands-on exercises, and Jupyter notebooks on GitHub. 

Start learning

Learners have access to GitHub notebooks and slides to accompany the video lectures, which provide the ability to self-guide through lessons and hands-on activities. Go at your own pace and choose the lessons and topics that are most relevant to you.

Natural Language Processing

Natural Language Processing guided lectures

Course Summary

This course is designed to help you get started with Natural Language Processing (NLP) and learn how to use NLP in various use cases. It will cover topics such as text processing, regression and tree-based models, hyperparameter tuning, recurrent neural networks, attention mechanism, and transformers.

Course Content

Check out the GitHub page for detailed lesson breakdown, projects, notebooks, and more.

Tabular Data

Tabular Data guided lectures

Course Summary

Learn how to get started with tabular data (spreadsheet-like data) and the widely used machine learning techniques to manipulate tabular data. This course will cover topics such as feature engineering, tree-based models and ensembles, regression models, neural networks, and AutoML.

Course Content

Check out the GitHub page for detailed lesson breakdown, projects, notebooks, and more.

Computer Vision

Computer Vision guided lectures

Course Summary

Through this course, you will gain the necessary skills to get started with computer vision. You will learn about image classification, convolutional neural networks, transfer learning, object detection, and semantic segmentation. 

Course Content

Check out the GitHub page for detailed lesson breakdown, projects, notebooks, and more.

Decision Trees and Ensemble Methods

Decision Trees and Ensemble Methods guided lectures

Course Summary

Get started with tree-based and ensemble models in this class. In this course you will learn about decision trees, impurities, bias-variance trade-off, random forests, proximities, feature importance, and boosting.

Course Content

Check out the GitHub page for detailed lesson breakdown, projects, notebooks, and more.

More Resources

Machine Learning Deep Dive

Advance your knowledge and skills of AWS ML Services. 

AWS Training and Certification

Explore guided courses and trainings for all levels of ML experience from AWS Training and Certification. 

Hands-on Tutorials

Use these quick tutorials to get started with AWS ML services and their common use cases.