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Our Courses
AWS Data Engineering Training Course
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Description Of Course Description Of Course Description Of Course Description Of Course Description Of Course Description Of Course
Course 1: Data Engineering using AWS Analytics Services
Introduction
Setup Local Environment for Practice
Version Controlling: Git and GitHub
Setup Environment for Practice using Cloud9
AWS Getting Started
Storage - All about AWS s3 (Simple Storage Service)
User Level Security
nfrastructure - AWS EC2 (Elastic Cloud Compute) Basics
Infrastructure - AWS EC2 Advanced
Data Ingestion using Lambda Functions
Development Lifecycle for Pyspark
Overview of Glue Components
Setup Spark History Server for Glue Jobs
Deep Dive into Glue Catalog
Exploring Glue Job APIs
Glue Job Bookmarks
Getting Started with AWS EMR
Deploying Spark Applications using AWS EMR
Streaming Pipeline using Kinesis
Consuming Data from s3 using boto3
Populating GitHub Data to Dynamodb
Overview of Amazon Athena
Amazon Athena using AWS CLI
Amazon Athena using Python boto3
Getting Started with Amazon Redshift
Copy Data from s3 into Redshift Tables
Develop Applications using Redshift Cluster
Redshift Tables with Distkeys and Sortkeys
Redshift Federated Queries and Spectrum
Course 2: Data Engineering, Serverless ETL & BI on Amazon Cloud
About the Course & Introduction
Getting Started with Redshift and MySql RDS
ETL and Syncing Traditional Data with Redshift DWH
Data Lakes & Handling External Data Sources
Redshift Spectrum
Quicksight - BI Reporting and Visualization
Redshift Optimization Techniques and Fine Tuning
Do more with AWS Glue
Course Features
Course Duration:
Real time Projects:
Course Material:
Resume Preparation:
Why Us?
ABOUT US
Our company's culture has always been to prioritize human capital growth. As a global consultancy firm, we work collaboratively with organizations to understand their business goals.
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