Author: Andrew Burchill; Difficulty: Beginner; Description: In this hands-on lab, you will work with regular expressions, learning how to use quantifiers, anchors, and capture groups to match patterns in text.; Duration: Up to 30 minutes; Content Topics: Development; This hands-on lab has: 2 Lab steps

Author: Logan Rakai; Difficulty: Beginner; Description: This lab uses Amazon SageMaker to create a machine learning model that forecasts flight delays for US domestic flights.; Duration: Up to 1 hour and 30 minutes; Content Topics: Machine Learning; This hands-on lab has: 7 Lab steps

Author: Greg DeRenne; Difficulty: Intermediate; Description: Learn how to create an Amazon EMR (Elastic MapReduce) cluster and submit work to a cluster in this hands-on lab.; Duration: Up to 1 hour and 45 minutes; Content Topics: Analytics, Storage; This hands-on lab has: 7 Lab steps

Author: Andrew Burchill; Difficulty: Beginner; Description: Learn how to implement object detection on every new image uploaded on Amazon S3.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 7 Lab steps

Author: Andrew Burchill; Difficulty: Beginner; Description: Regular expressions are a powerful tool for searching and manipulating text. In this hands-on lab you will learn how to use them effectively in real-world scenarios.; Duration: Up to 1 hour; Content Topics: Development; This hands-on lab has: 2 Lab steps

Author: Andrew Burchill; Difficulty: Beginner; Description: In this hands-on lab, you will learn about the character classes and quantifiers elements of Regular Expressions, and use them to match patterns in text.; Duration: Up to 30 minutes; Content Topics: Development; This hands-on lab has: 2 Lab steps

Author: Matt Martinez; Difficulty: Beginner; Description: Use the AI Services API in the Azure AI suite to perform text analytics operations by requesting the API services via an Azure Function App.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 5 Lab steps

Author: Logan Rakai; Difficulty: Intermediate; Description: In this lab, you'll use a SageMaker notebook to learn how to write Python code to prepare data, train and deploy models, and use them for real-time inference.; Duration: Up to 1 hour; Content Topics: Amazon Web Services; This hands-on lab has: 4 Lab steps

Author: Logan Rakai; Difficulty: Intermediate; Description: Develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI in this Lab.; Duration: Up to 1 hour and 40 minutes; Content Topics: Machine Learning; This hands-on lab has: 9 Lab steps

Author: Logan Rakai; Difficulty: Intermediate; Description: Join this Lab and gain experience using an MXNet convolutional neural network to style images and monitor the GPU used for training in Amazon CloudWatch.; Duration: Up to 1 hour and 10 minutes; Content Topics: Machine Learning; This hands-on lab has: 7 Lab steps

Author: Logan Rakai; Difficulty: Beginner; Description: Take control of a p2.xlarge instance equipped with an NVIDIA Tesla K80 GPU to perform CPU vs GPU performance analysis for AWS Machine Learning in this Lab.; Duration: Up to 45 minutes; Content Topics: Machine Learning; This hands-on lab has: 8 Lab steps

Author: Calculated Systems; Difficulty: Beginner; Description: This lab is aimed at machine learning beginners who want to understand how to train custom models.; Duration: Up to 3 hours; Content Topics: Machine Learning; This hands-on lab has: 3 Lab steps

Author: Thomas Holmes; Difficulty: Beginner; Description: This Lab provides you with a Jupyter notebook that introduces you to basic concepts in Python by explaining concepts and letting you write and run Python code.; Duration: Up to 2 hours; Content Topics: Development; This hands-on lab has: 2 Lab steps

Author: Logan Rakai; Difficulty: Beginner; Description: This playground lab allows you to choose from Amazon's curated library of sample notebooks to learn about what is most important to you.; Duration: Up to 2 hours; Content Topics: Machine Learning; This hands-on lab has: 4 Lab steps

Author: Kunal Haria; Difficulty: Beginner; Description: This lab includes several modules for you to work through to cement your R fundamentals proficiency.; Duration: Up to 8 hours; This hands-on lab has: 2 Lab steps

Author: Calculated Systems; Difficulty: Intermediate; Description: This lab will walk you through a number of ways to handle missing data including using a default value and building a model to predict the missing data.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 4 Lab steps

Author: Andrea Giussani; Difficulty: Beginner; Description: In this lab, you will learn how to create a dataset using the PySpark library, and to manipulate it using standard filtering and slicing techniques.; Duration: Up to 1 hour; Content Topics: Development; This hands-on lab has: 2 Lab steps

Author: Calculated Systems; Difficulty: Intermediate; Description: This lab walks you through building several multivariate linear regression models using different prediction variables and evaluating the models' predictions.; Duration: Up to 43 minutes; Content Topics: Machine Learning; This hands-on lab has: 4 Lab steps

Author: Calculated Systems; Difficulty: Intermediate; Description: This lab will walk you through building several binary classification models using different model methodologies and then comparing the model predictions using evaluation tools.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 4 Lab steps

Author: Calculated Systems; Difficulty: Beginner; Description: How do you know that your models will do a good job making predictions on new, unseen data? This lab will discuss the fundamentals.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 4 Lab steps

Author: Stefano Cascavilla; Difficulty: Intermediate; Duration: Up to 45 minutes; Content Topics: Machine Learning; This hands-on lab has: 5 Lab steps

Author: Calculated Systems; Difficulty: Beginner; Description: This lab is aimed at beginners who want to move beyond spreadsheets and migrate their data into a database.; Duration: Up to 1 hour and 20 minutes; Content Topics: SQL; This hands-on lab has: 3 Lab steps

Author: Thomas Holmes; Difficulty: Beginner; Description: You will put your basic knowledge of Python to work in this lab challenge in order to perform a simple form of data cleansing on text.; Duration: Up to 2 hours and 30 minutes; Content Topics: Development; This lab challenge has: 2 Lab steps

Author: Calculated Systems; Difficulty: Beginner; Description: Learn how to create a simulated banking concierge bot using Google DIalogflow in this lab.; Duration: Up to 1 hour; Content Topics: Artificial Intelligence; This hands-on lab has: 9 Lab steps