AWS Data Engineer Course & Curriculum

NCPL's hands-on AWS Data Engineer training — full curriculum, real projects, certification prep, and job placement support. We train, mentor and place you.

Module 1: Introduction to AWS Cloud & Data Engineering

Explore cloud computing fundamentals and AWS basics.

  • Overview of Cloud Computing and AWS
  • IAM, Security Groups, and Policies
  • AWS Networking Basics (VPCs, Subnets)
  • AWS CLI and Boto3 SDK

Module 2: Data Storage on AWS

Learn about S3, DynamoDB, RDS, and data storage solutions.

  • Amazon S3 Basics and Storage Classes
  • S3 Lifecycle Policies
  • DynamoDB NoSQL Database
  • RDS and Aurora for Relational Data

Module 3: Data Integration with AWS Glue & Lambda

Master ETL processes and serverless computing.

  • AWS Glue Data Cataloging
  • ETL Script Writing with Glue
  • Workflow Automation
  • AWS Lambda for Serverless Computing
  • Event-Driven Architectures
  • Lambda Integration with S3 and DynamoDB

Module 4: Data Warehousing on AWS

Dive into Amazon Redshift and data warehouse solutions.

  • Amazon Redshift Basics
  • Cluster Setup and Configuration
  • Redshift Spectrum for S3 Queries
  • Query Optimization Techniques

Module 5: Real-time Data Streaming with AWS Kinesis

Explore real-time data processing and analytics.

  • Kinesis Overview and Concepts
  • Data Streams Setup and Producers
  • Kinesis Analytics for Real-time Processing
  • Lambda Integration with Kinesis

Module 6: Data Processing with AWS EMR

Learn big data processing with Hadoop and Spark.

  • EMR and Hadoop Basics
  • Apache Spark on EMR
  • EMR Cluster Configuration
  • Complex Data Processing Workflows

Module 7: Data Querying and Analytics on AWS

Master QuickSight and Athena for data analysis.

  • AWS QuickSight Introduction
  • Data Visualization and Dashboards
  • Athena for Ad Hoc SQL Queries
  • Advanced Analytics with ML Insights

Module 8: Data Governance and Security on AWS

Implement robust security and compliance measures.

  • IAM and KMS for Access Control
  • CloudTrail for Monitoring and Auditing
  • AWS Config for Compliance
  • Data Encryption Best Practices

Module 9: Databricks on AWS

Explore Databricks integration with AWS services.

  • Databricks Architecture on AWS
  • Workspace Setup and Configuration
  • Data Engineering with Notebooks
  • Integration with AWS Services

Module 10: Airflow & PySpark

Learn workflow automation and distributed computing.

  • Apache Airflow Introduction
  • DAG Writing for Workflow Automation
  • PySpark Basics and Distributed Computing
  • Airflow-PySpark Integration