- Introduction
- Definition of Data Analytics
- Data Classification
- The 3 V's of Big Data
- Analytics Evolution
- The Analytics Problem Approach
- AWS Big Data and Analytics - Collect
- AWS Big Data and Analytics - Storage
- AWS Big Data and Analytics - Process and Analyze
- Amazon Kinesis Overview
- Kinesis Three Services
- Kinesis Analytics Summary & Scenarios
- Time Series Analytics to Kibana
- Mobile App to RedShift & QuickSight
- IoT Real-Time Monitoring
- Kinesis Analytics Benefits
- Kinesis Analytics Application
- Kinesis Analytics Application Inputs, SQL, & Outputs
- Kinesis Analytics SQL Editor
- SQL Query Templates
- Continuous Filter
- Aggregate Function Tumbling Time
- Multi-Step Application
- Query Structure
- Application Pump - Create Stream
- Application Pump - Create Pump
- Continuous Queries
- Query Windows
- Tumbling, Sliding, & Custom Windows
- Introduction to Amazon EMR
- EMR Use Cases
- EMR Ecosystem
- EMR Node Types
- EMR Resizable Clusters
- EMR Storage Connectivity
- EMR Networking
- EMR Networking - Bastion Host
- EMR Networking - VPC
- Launching Cluster
- Create Cluster - Quick Options
- Key Objective of Machine Learning
- Arthur Samuel Machine Learning Definition
- Tom Mitchell Machine Learning Formal Definition
- Industry Application
- Terminology
- Terminology Examples
- Machine Learning Phases
- Machine Learning Types
- Supervised Learning Definition
- Supervised Learning Process
- Classification Vs. Regression
- Supervised Learning Algorithms
- Supervised Training Process
- Business Analytics
- Training Summary
- Unsupervised Learning Introduction
- Unsupervised Learning Definition
- Pattern Types
- Clustering
- Anomaly Detection
- Association Discovery
- Clustering Example
- Unsupervised Training Process
- Unsupervised Learning Business Analytics
- Unsupervised Learning Dataset Summary
- Unsupervised Learning Training Summary
- Splitting Your Dataset
- Training a Model
- Important Practices While Training Your Model
- Important Practices While Training Your Model Pt. 2
- Important Practices While Training Your Model Pt. 3