This module introduces the fundamentals of cloud computing and foundational AWS services. Students will learn the core concepts and terminology of cloud computing, gain an understanding of the AWS global infrastructure, and explore the basic AWS operations. The module provides an essential foundation for those new to AWS and cloud computing, establishing the knowledge base required for more advanced topics in subsequent modules.

This module delves into the networking aspects of AWS, covering network design, implementation, management, security, compliance, and governance. Students will learn how to architect and configure Amazon VPC (Virtual Private Cloud), set up subnets, route tables, and internet gateways, implement security groups and network ACLs, and establish connectivity between different network environments. The module also addresses network monitoring, optimization, and troubleshooting on AWS.

This module focuses on AWS security services and best practices for creating secure cloud environments. Students will learn about threat detection, logging and monitoring, infrastructure security, identity and access management (IAM), data protection, and security management on AWS. The module covers implementation of security controls, compliance frameworks, encryption mechanisms, and security incident response, equipping students with the knowledge to protect cloud resources and data from various threats.

This advanced module prepares students for designing complex AWS solutions in enterprise environments. It addresses organizational complexity, designing new solutions, continuous improvement strategies, and accelerating workload migration and modernization on AWS. Students will learn architectural patterns for high availability, fault tolerance, and scalability, as well as cost optimization techniques and multi-account management strategies. This module aligns with the knowledge areas required for the AWS Certified Solutions Architect - Professional certification.

This module explores AWS services and architectures for data analytics workloads. Students will learn about data collection methods, storage and data management options, processing frameworks, analysis and visualization tools, and security considerations for data analytics on AWS. The module covers services like Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Kinesis, and AWS Glue, providing hands-on experience with building and operating data analytics solutions in the cloud.

This module focuses on implementing machine learning solutions on AWS. Students will learn about data engineering practices, exploratory data analysis techniques, modeling approaches, and machine learning implementation and operations on AWS. The module covers services like Amazon SageMaker, Amazon Comprehend, Amazon Rekognition, and Amazon Forecast, providing practical knowledge of building, training, deploying, and managing machine learning models in the cloud environment.