Cloud Data Engineering with AWS

Cloud Data Engineering with AWS offers a comprehensive exploration of data pipeline creation, management, and optimization in cloud environments. Participants will engage with practical, project-based learning, focusing on real-world applications of AWS tools and services. The course emphasizes hands-on experience, enabling learners to construct robust data architectures and effectively manage data workflows within the cloud.
Throughout the course, students will delve into various aspects of data engineering, including the design of data pipelines, data storage solutions, and data transformation processes. By the end of the program, participants will have the opportunity to publish their project results in Cademix Magazine, showcasing their newly acquired skills and enhancing their professional profiles. The curriculum is structured to ensure that learners not only gain theoretical knowledge but also apply their learning to solve practical challenges in cloud data engineering.
Introduction to Cloud Computing and AWS
Data Engineering Fundamentals and Best Practices
AWS Data Storage Solutions: S3, RDS, and DynamoDB
Building Data Pipelines with AWS Glue
ETL Processes: Extract, Transform, Load Techniques
Real-Time Data Processing with AWS Kinesis
Data Warehousing with Amazon Redshift
Monitoring and Logging Data Pipelines using AWS CloudWatch
Security and Compliance in AWS Data Engineering
Final Project: Designing and Implementing a Complete Data Pipeline on AWS

Equip participants with the skills to design, implement, and manage data pipelines using AWS services effectively.

Graduates, job seekers, business professionals, and optionally researchers or consultants.

Basic understanding of cloud computing concepts and familiarity with programming (Python or SQL preferred).