Data Engineering Foundations on AWS Certified Course

The Amazon Web Services Data Engineering Foundations on AWS Certified Course is designed to provide a strong foundation in modern data engineering concepts using cloud-based technologies. This program introduces learners to the core principles of data processing, storage, and analytics while leveraging powerful AWS services.

This course equips students with the skills required to design, build, and manage scalable data pipelines, data lakes, and data warehouses in a cloud environment. Learners will gain hands-on experience with industry-relevant tools and understand how to work with structured, semi-structured, and unstructured data.

Through practical labs, real-world use cases, and guided projects, participants will learn how to implement ETL (Extract, Transform, Load) processes, ensure data quality, and apply security best practices in AWS. The course also aligns with the AWS Certified Data Engineer – Associate exam objectives, helping learners prepare for globally recognized certification.

By the end of this program, learners will have a solid understanding of AWS data services, cloud architecture, and data engineering workflows, enabling them to build efficient, scalable, and secure data solutions for modern businesses.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities After Data Engineering Foundations on AWS:

• Data Engineer – Design and build scalable data pipelines and data infrastructure
• AWS Data Engineer – Work specifically with AWS services like S3, Glue, Redshift, and Lambda
• Cloud Data Engineer – Manage and optimize cloud-based data architectures
• Big Data Engineer – Handle large-scale distributed data processing systems
• ETL Developer – Develop data extraction, transformation, and loading workflows
• Data Analyst (Advanced) – Analyze and visualize data using cloud tools
• Data Architect (Entry-Level) – Design data models and cloud data solutions
• Machine Learning Data Engineer – Prepare and manage datasets for ML models
• Analytics Engineer – Bridge the gap between data engineering and analytics

Essential Skills You Will Develop Data Engineering Foundations on AWS:

• Data Pipeline Development – Design and implement scalable ETL/ELT pipelines for data processing
• Cloud Data Storage – Work with data lakes and warehouses using services like S3 and Redshift
• ETL & Data Transformation – Clean, transform, and prepare raw data for analysis
• Big Data Processing – Handle large datasets using distributed computing concepts
• AWS Data Services Expertise – Gain hands-on experience with Glue, Lambda, Kinesis, and EMR
• SQL & Query Optimization – Write efficient queries for data extraction and performance tuning
• Data Modeling – Design structured schemas for analytics and reporting
• Data Security & Governance – Implement IAM roles, encryption, and compliance best practices
• Workflow Orchestration – Automate pipelines using scheduling and orchestration tools
• Real-Time Data Processing – Work with streaming data and event-driven architectures

Tools Covered:

• Amazon S3 – Scalable storage for data lakes and raw data
• AWS Glue – ETL service for data preparation and transformation
• Amazon Redshift – High-performance data warehousing and analytics
• Amazon RDS – Managed relational databases (MySQL, PostgreSQL, etc.)
• Amazon DynamoDB – Fast and flexible NoSQL database for real-time applications
• AWS Lambda – Event-driven data processing without managing servers
• Amazon Kinesis – Streaming and processing real-time data
• Amazon EMR – Big data processing using Hadoop and Spark

Syllabus:

Module 1: Introduction to Data Engineering & Cloud

• Fundamentals of data engineering
• Types of data: structured, semi-structured, unstructured
• Introduction to cloud computing and AWS ecosystem

Module 2: AWS Core Services Overview

• Overview of AWS global infrastructure
• Introduction to key services like Amazon S3, Amazon EC2
• Understanding pricing and cost management basics

Module 3: Data Storage Solutions

• Building data lakes using Amazon S3
• Working with relational databases using Amazon RDS
• NoSQL databases with Amazon DynamoDB

Module 4: Data Warehousing

• Introduction to data warehousing concepts
• Working with Amazon Redshift
• Data modeling and schema design

Module 5: ETL & Data Processing

• ETL concepts and workflows
• Data transformation using AWS Glue
• Introduction to Apache Spark for big data processing

Module 6: Big Data & Distributed Systems

• Big data fundamentals and ecosystem
• Working with Amazon EMR
• Batch vs real-time processing

Module 7: Real-Time Data Streaming

• Streaming concepts and use cases
• Data ingestion using Amazon Kinesis
• Event-driven processing with AWS Lambda

Module 8: Workflow Orchestration

• Building data pipelines and workflows
• Automation using AWS Step Functions
• Scheduling and dependency management

Module 9: Data Security & Governance

• Identity and access management using AWS IAM
• Data encryption and compliance
• Best practices for secure data pipelines

Module 10: Monitoring & Optimization

• Monitoring pipelines with Amazon CloudWatch
• Performance tuning and cost optimization
• Troubleshooting data workflows

Industry Projects:

• End-to-end ETL pipeline using Amazon S3, AWS Glue, and Amazon Redshift
• Real-time data streaming project with Amazon Kinesis and AWS Lambda
• Data lake architecture design using Amazon S3
• Big data processing using Amazon EMR and Apache Spark
• Data warehouse optimization in Amazon Redshift
• Serverless workflow automation with AWS Step Functions
• Secure data pipeline implementation using AWS IAM
• Monitoring and logging using Amazon CloudWatch
• SQL-based data analysis and reporting using SQL

Who is this program for?

• Aspiring Data Engineers who want to build a career using Amazon Web Services
• Fresh graduates in engineering, computer science, or IT looking to enter the data domain
• Software developers who want to transition into data engineering roles
• Data analysts aiming to upgrade to cloud-based data engineering skills
• Database administrators interested in modern cloud data platforms
• IT professionals seeking to learn big data and cloud technologies
• Professionals preparing for AWS certifications in data engineering
• Big data enthusiasts who want hands-on experience with real-world tools

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com