Author: Calculated Systems; Difficulty: Intermediate; Duration: 42 minutes and 22 seconds; Content Topics: Databases; This course has: 16 Units

Author: Andrea Giussani; Difficulty: Intermediate; Description: A deep dive into the visualization tools and libraries available in Python.; Duration: Up to 6 hours and 28 minutes; Content Topics: Analytics, Development; This learning path has: 3 Courses, 1 Exam, 2 Hands-on labs

Author: Guy Hummel; Difficulty: Intermediate; Description: This course will introduce you to the primary machine learning tools on Azure.; Duration: Up to 5 hours and 1 minute; Content Topics: Microsoft Azure; This learning path has: 1 Course, 2 Hands-on labs

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: Amazon Web Services; This hands-on lab has: 7 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: Andrew Burchill; Difficulty: Beginner; Description: Learn how to use Amazon Bedrock to run an automated model evaluation in this hands-on lab.; Duration: Up to 1 hour; Content Topics: Storage, Artificial Intelligence; 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: Amazon Web Services; This hands-on lab has: 9 Lab steps

Author: Logan Rakai; Difficulty: Intermediate; Description: Join this Lab and gain experience using an TensorFlow 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: Amazon Web Services; This hands-on lab has: 6 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: Amazon Web Services; This hands-on lab has: 8 Lab steps

Author: Kunal Haria; Difficulty: Intermediate; Duration: 24 minutes and 24 seconds; Content Topics: Machine Learning; This course has: 4 Units

Author: Kunal Haria; Difficulty: Intermediate; Duration: 37 minutes and 39 seconds; Content Topics: Machine Learning; This course has: 9 Units

Author: Kunal Haria; Difficulty: Intermediate; Duration: 20 minutes and 52 seconds; Content Topics: Development; This course has: 7 Units

Author: Farish Kashefinejad; Difficulty: Beginner; Duration: 11 minutes and 47 seconds; Content Topics: Artificial Intelligence; This course has: 1 Unit

Author: Francesco Mosconi; Difficulty: Beginner; Duration: 1 hour and 2 minutes; Content Topics: Machine Learning; This course has: 17 Units

Author: Francesco Mosconi; Difficulty: Beginner; Duration: 45 minutes and 15 seconds; Content Topics: Machine Learning; This course has: 12 Units

Author: Francesco Mosconi; Difficulty: Beginner; Duration: 1 hour and 19 minutes; Content Topics: Machine Learning; This course has: 22 Units

Author: Emilio Melo; Difficulty: Intermediate; Duration: 48 minutes and 37 seconds; Content Topics: Microsoft Azure; This course has: 10 Units

Author: QA; Difficulty: Intermediate; Description: Practical Machine Learning; Duration: Up to 19 hours and 1 minute; Content Topics: Amazon Web Services, Microsoft Azure; This learning path has: 11 Courses, 6 Exams, 2 Hands-on labs

Author: Danny Jessee; Difficulty: Intermediate; Description: Train to prepare for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam; Duration: Up to 80 hours and 11 minutes; Content Topics: Amazon Web Services; This learning path has: 71 Courses, 11 Exams, 16 Hands-on labs

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 1 hour and 30 minutes; Content Topics: Amazon Web Services; This hands-on lab has: 3 Lab steps

Author: Andrea Giussani; Difficulty: Beginner; Description: The aim of this lab is to challenge you on building a supervised machine learning pipeline to predict the median values of owner-occupied housing in USD 1000 in the Boston dataset.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 2 Lab steps