Overall Duration : 136 Hours Content of This Course Introduction 15:24 Course Introduction About The Exam About This Course Data Collection 01:01:58 Introduction Concepts General Data Terminology Machine Learning Data Terminology AWS Data Stores AWS Migration Tools AWS Helper Tools Exam Tips Streaming Data Collection 01:11:47 Introduction Concepts Kinesis Data Streams Kinesis Firehose Kinesis Video Streams Kinesis Data Analytics Exam Tips Data Preparation 01:50:54 Introduction Concepts Categorical Encoding Text Feature Engineering Numeric Feature Engineering Other Feature Engineering Handling Missing Values Feature Selection Helper Tools Exam Tips Data Analysis and Visualization 01:16:38 Introduction Concepts Relationships Comparisons Distributions Compositions Choosing A Visualization Exam Tips Data Analysis and Visualization Lab Modeling 01:22:11 Introduction Concepts Data Preparation SageMaker Modeling SageMaker Training Exam Tips Algorithms 02:20:49 Introduction OPTIONAL - Why do we call them "Algorithms"? Concepts Regression Clustering Classification Image Analysis Anomaly Detection Text Analytics Reinforcement Learning Forecasting Ensemble Learning Evaluation and Optimization 01:15:24 Introduction Concepts Monitoring and Analyzing Training Jobs Evaluating Model Accuracy Model Tuning Exam Tips Implementation and Operations 01:37:56 Introduction Concepts AI Developer Services Amazon SageMaker Deployments Other ML Deployment Options Security Monitor and Evaluate Exam Tips Wrap-Up 00:47
