This section equips students with a deep understanding of AWS Identity and Access Management (IAM), focusing on secure, scalable access control strategies. Learners will:

• Grasp the core purpose of IAM and its role in managing authentication and authorization across AWS services.
• Create and manage IAM users and groups, applying least privilege principles to organize access efficiently.
•  Write and attach IAM policies using JSON syntax, learning how to define granular permissions and evaluate policy effects.
• Explore IAM roles for cross-service access, temporary credentials, and secure delegation between AWS resources.
•  Apply best practices like MFA enforcement and avoiding root user reliance to build secure environments.

By the end of this section, students will be able to design and implement robust IAM strategies that support secure operations and scalable team collaboration.

This section guides students through the architecture and security of Amazon Virtual Private Cloud (VPC), empowering them to design isolated, secure, and scalable network environments. Learners will:

•  Understand the purpose and structure of VPCs, including CIDR blocks, IP addressing, and default vs. custom VPCs.

• Dive into subnets—public and private—and configure them for controlled access to resources.

• Explore route tables and learn how traffic is directed within and between subnets, with hands-on practice.

• Configure security groups and network ACLs to enforce fine-grained traffic control, comparing stateful and stateless behavior.

• Implement VPC peering to enable secure communication between VPCs across accounts or regions.

By the end of this section, students will be able to build and secure multi-tier architectures using VPC components and apply best practices for segmentation and access control.

This section introduces students to AWS storage services, with a focus on Amazon S3 and its practical applications. Learners will:

• Understand the range of AWS storage offerings and their use cases, including object, block, and file storage.

• Explore Amazon S3’s key features such as durability, scalability, and global accessibility.

• Create and configure S3 buckets, including naming conventions, region selection, and access settings.

• Upload and manage objects within S3 buckets, using the console.

• Compare S3 storage classes and select appropriate options based on access frequency and cost-efficiency.

• Implement lifecycle policies to automate transitions between storage classes and manage data retention.

• Gain exposure to other AWS storage services like EBS, EFS, and Glacier, understanding when and why to use each.

By the end of this section, students will be able to architect storage solutions that balance performance, cost, and data management needs.

This section introduces students to AWS database services, focusing on both relational and NoSQL options, along with hands-on experience in provisioning and querying. Learners will:

• Understand the differences between relational and non-relational databases, and when to use each.

• Explore Amazon RDS and Amazon Aurora, including automated backups and replication.

• Launch and configure RDS and Aurora instances, connect to them securely, and execute SQL scripts for data manipulation.

• Practice writing and running SQL queries to create tables, insert data, and retrieve results.

• Learn about Amazon DynamoDB, its key-value and document data model, and use cases for high-performance NoSQL workloads.

• Perform hands-on tasks with DynamoDB, including table creation, item insertion, and query operations.

By the end of this section, students will be able to choose appropriate AWS database services based on workload requirements, deploy and connect to managed databases, and perform basic data operations using SQL and DynamoDB.

This section introduces students to AWS compute services, focusing on both virtual server provisioning and serverless architecture. Learners will:

• Understand the role of compute in cloud environments and the differences between traditional and serverless models.

• Launch and configure Amazon EC2 instances, including selecting AMIs, instance types and security groups.

• Connect to EC2 instances

• Explore AWS Lambda as a serverless compute service, including its event-driven model and integration with other AWS services.

• Build and deploy Lambda functions

By the end of this section, students will be able to provision virtual machines, deploy serverless functions, and choose appropriate compute options based on workload characteristics.