★★★★★
"The structure, the practice exams, the instructor — all top tier. Passed first try."
AS
Aarti SharmaSenior Project Manager · TCS
— The journey
Course Outline
What the programme covers, module by module.
Module 1: Introduction to AWS Data Engineering
- Cloud data engineering
- AWS ecosystem
- Data lifecycle
- Data architecture
- Analytics overview
- Industry use cases
Module 2: AWS Core Services
- IAM
- EC2
- VPC
- S3
- CloudWatch
- AWS Management Console
Module 3: Amazon S3
- Buckets
- Object storage
- Versioning
- Lifecycle policies
- Storage classes
- Security
Module 4: Data Ingestion
- Batch ingestion
- Streaming ingestion
- AWS DataSync
- AWS Transfer Family
- Data migration
- Data integration
Module 5: AWS Glue
- Glue Data Catalog
- Crawlers
- ETL jobs
- Glue Studio
- Data transformation
- Workflow automation
Module 6: AWS Lambda
- Serverless functions
- Event-driven processing
- Automation
- Scheduling
- Integrations
- Performance optimization
Module 7: Amazon Kinesis
- Data streams
- Real-time analytics
- Stream processing
- Data producers
- Consumers
- Monitoring
Module 8: Amazon EMR
- Hadoop ecosystem
- Spark
- Hive
- Big data processing
- Cluster management
- Performance tuning
Module 9: Amazon Redshift
- Data warehouse concepts
- Cluster creation
- Query optimization
- Data loading
- Performance tuning
- Reporting
Module 10: Amazon Athena
- Serverless querying
- SQL on S3
- Partitioning
- Query optimization
- Analytics
- Reporting
Module 11: Amazon RDS & Aurora
- Relational databases
- Database migration
- Backup
- Replication
- Performance optimization
- Security
Module 12: Amazon DynamoDB
- NoSQL concepts
- Tables
- Indexes
- Capacity planning
- Performance
- Best practices
Module 13: ETL Pipeline Development
- Data extraction
- Data transformation
- Data loading
- Workflow orchestration
- Scheduling
- Error handling
Module 14: Data Lakes
- Lake architecture
- AWS Lake Formation
- Metadata management
- Governance
- Data cataloging
- Security
Module 15: Data Warehousing
- Warehouse design
- Dimensional modeling
- Fact tables
- Star schema
- Snowflake schema
- Optimization
Module 16: Data Processing with Spark
- Spark fundamentals
- Spark SQL
- DataFrames
- Transformations
- Performance tuning
- Cluster execution
Module 17: Workflow Orchestration
- AWS Step Functions
- EventBridge
- Workflow automation
- Scheduling
- Dependencies
- Monitoring
Module 18: Security & Governance
- IAM policies
- Encryption
- KMS
- Data privacy
- Compliance
- Security best practices
Module 19: Monitoring & Logging
- CloudWatch
- CloudTrail
- Logging
- Metrics
- Alerts
- Troubleshooting
Module 20: Performance Optimization
- Query optimization
- Cost optimization
- Partitioning
- Compression
- Caching
- Resource tuning
Module 21: DevOps for Data Engineering
- Infrastructure as Code
- CI/CD
- Version control
- Deployment pipelines
- Automation
- Best practices
Module 22: Machine Learning Data Pipelines
- Data preparation
- Feature engineering
- Amazon SageMaker integration
- Model pipelines
- Data quality
- Workflow automation
Module 23: Business Intelligence Integration
- Amazon QuickSight
- Dashboard creation
- Reporting
- KPI visualization
- Business analytics
- Decision support
Module 24: Streaming Analytics
- Real-time dashboards
- Event processing
- Stream analytics
- Alerting
- Monitoring
- Business use cases
Module 25: Disaster Recovery & Backup
- Backup strategies
- Cross-region replication
- High availability
- Recovery planning
- Business continuity
- Testing
Module 26: Real-World Data Engineering Projects
- Customer analytics
- Sales analytics
- IoT data pipelines
- Financial analytics
- Log analytics
- Practical exercises
Module 27: Enterprise Data Architecture
- Data governance
- Metadata management
- Enterprise integration
- Data quality
- Architecture best practices
- Documentation
Module 28: Industry Best Practices
- Cloud architecture
- Secure pipelines
- Scalability
- Reliability
- Operational excellence
- Cost management
Module 29: Capstone Project
- End-to-end data pipeline
- ETL implementation
- Analytics solution
- Performance optimization
- Documentation
- Project presentation
Module 30: Career Development & Future Trends
- Data engineering roadmap
- Emerging AWS services
- AI-powered data engineering
- Professional growth
- Industry trends
- Continuous learning
— 01.2 · Is it right for you?
Who it's for & what's included
Pick a delivery method to see exactly who it suits and everything you receive.
Who it's for
Classroom
Best for learners who want face-to-face tuition and to network with peers in person.
What's included
Everything you get
- ✓ Live instructor on-site
- ✓ Printed workbook & materials
- ✓ Group exercises & case studies
Who it's for
Online Instructor-Led
Best for learners who want a live instructor and a fixed schedule, without the travel.
What's included
Everything you get
- ✓ Live instructor via video call
- ✓ Digital workbook & resources
- ✓ Session recordings
Who it's for
Self-Paced
Best for self-motivated learners who need maximum flexibility around work and life.
What's included
Everything you get
- ✓ On-demand video lessons
- ✓ Interactive quizzes
- ✓ 24/7 access on any device