- Introduction to AWS Machine Learning – Specialty Certification Preparation
- Introduction to Machine Learning Concepts
- Introduction to Data and Machine Learning
- Module 0 – What is Machine Learning? – Part One
- Module 0 – What is Machine Learning? – Part Two
- Knowledge Check: Practical Machine Learning – Module 0
- Working with Distributed Machine Learning
- TensorFlow Machine Learning on the Amazon Deep Learning AMI
- Analyzing CPU vs GPU Performance for AWS Machine Learning
- Module 1 – Python for Machine Learning
- Knowledge Check: Practical Machine Learning – Module 1
- Module 2 – Maths for Machine Learning – Part One
- Module 2 – Maths for Machine Learning – Part Two
- Knowledge Check: Practical Machine Learning – Module 2
- Introduction to Deep Learning
- Getting Started with Deep Learning: Introduction To Machine Learning
- Getting Started With Deep Learning: Working With Data
- Getting Started With Deep Learning: Working With Data: Gradient Descent
- Knowledge Check: Zero to Deep Learning – Introduction to Deep Learning
- Knowledge Check: Zero to Deep Learning – Introduction to Data Science and
- Machine Learning
- Getting Started With Deep Learning: Convolutional Neural Networks
- Getting Started With Deep Learning: Recurrent Neural Networks
- Getting Started With Deep Learning: Improving Performance
- Knowledge Check: Zero to Deep Learning – Working with Convolutional and
- Recurrent Neural Networks
- Introduction to SageMaker
- Get Started with Amazon SageMaker Data Wrangler, Data Pipeline, Feature
- Store and Ground Truth
- Module 3 – Supervised Learning – Part One
- Module 3 – Supervised Learning – Part Two
- Knowledge Check: Practical Machine Learning – Module 3
- Using SageMaker Notebooks to Train and Deploy Machine Learning Models
- Amazon SageMaker Notebook Playground
- Forecast Flight Delays with Amazon SageMaker
- Knowledge Check: Start Modeling Data with Amazon SageMaker
- Module 4 – Model Selection
- Knowledge Check: Practical Machine Learning – Module 4
- Common Machine Learning Models & How to Train Them
- Machine Learning – Training Custom Models
- Evaluating Binary Classification Models
- Testing Your Models in the Real World
- Knowledge Check: Getting Started with Machine Learning Models
- Module 5 – Regression
- Evaluating Model Predictions for Regression Models
- Knowledge Check: Practical Machine Learning – Module 5
- Module 6 – Unsupervised learning
- Module 7 – Probability and statistics
- Introduction to Amazon Rekognition
- Handling Missing Data
- Automate Image Labeling with Amazon Rekognition
- Working with Amazon Lex – Chatbots
- Using an MXNet Neural Network to Style Images
- How AWS IAM is Used to Securely Manage Access
- Managing User Identities with Long Term Credentials in AWS IAM
- Managing Access using IAM User Groups & Roles
- Using IAM Policies to Define and Manage Permissions
- Advanced Roles and Groups Management Using IAM
- Knowledge Check: Overview of AWS Identity and Access Management (IAM)
- Storage Fundamentals for AWS
- Designing Secure Applications and Architectures
- Using Amazon S3 Bucket Properties & Management Features to Maintain Data
- Amazon S3: Data Replication and Bucket Key Encryption
- The Fundamentals of the AWS Key Management Service (KMS)
- Securing Access to Your AWS KMS Keys
- Knowledge Check: AWS Storage Fundamentals
- AWS Step Functions
- Introduction to AWS Step Functions
- Analyzing Data with Amazon Athena
- Query Encrypted Amazon S3 Data with Amazon Athena
- Developing Serverless ETL with AWS Glue
- Overview of Amazon Kinesis
- Working with Amazon Kinesis Analytics