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Our Courses

AWS Data Engineering Training Course

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


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?


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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