
AWS Big Data Analytics
Duration: 15 Weeks
Audience: Business Analysts, IT Architects, Technical Managers and Developers
Suggested Prerequisites: Big Data Hadoop, Spark & Kafka
Topics:
Outline of Course TRAINING:
Week 1
- Introduction
- Data Engineering & Data Science
- The World of AWS Cloud
Week 2
- The World of AWS Cloud
- Walkthrough of AWS Project
Week 3 – Domain 1 – Collection, Domain 2 – Storage
- S3, Glacier and Snowball
Week 4 – Domain 1 – Collection, Domain 2 – Storage, Ingestion Zone – Streaming
- Kinesis Data Streams
- Kinesis Analytics
- Lambda & SES
Week 5 – Domain 3 – Processing, Domain 4 – Analysis, Domain 6 – Security
Analysis Zone, Monitoring Zone
- Kinesis Data Firehose
- Kinesis Agent
- Elasticsearch
Week 6 – Domain 1 – Collection, Domain 3 – Processing
Ingestion Zone – Database
- DMS
- Glue
Week 7 – Domain 1 – Collection, Domain 3 – Processing
Ingestion Zone – Files
- EMR
Week 8 – -Domain 3 – Processing
Curation Zone
- AWS Glue
Week 9 – Domain 3 – Processing
Transformation Zone
- Sagemaker
- Glue
Week 10 – Domain 1 – Collection, Domain 3 – Processing
Ingestion Zone – IoT
- AWS IoT Core
- AWS IoT Button
Week 11 – Domain 1 – Collection, Domain 4 – Analysis
Ingestion Zone – DynamoDB
- DynamoDB
Week 12 – Domain 4 – Analysis
Data Science Zone
- Sagemaker
- Jupyter Notebooks
Machine Learning Zone
- Machine Learning
Week 13 – Domain 4 – Analysis
Artificial Intelligence Zone
- Amazon Rekognition
- Amazon Polly
Week 14 – Domain 4 – Analysis
Discovery Zone
- Athena
- Redshift
Week 15 – Domain 5 – Visualization
Discovery Zone
- Quicksight
- Project Submission
- Final Test