AWS Foundational Certifications cover the knowledge needed to understand AWS Cloud services, terminology, security concepts, pricing, support, and AI use cases at an introductory level.

The current foundational credentials are AWS Certified Cloud Practitioner and AWS Certified AI Practitioner. These certifications suit business, technical, sales, project, product, and early-career cloud roles that need a common AWS knowledge base.

• AWS Certified Cloud Practitioner covers cloud concepts, security and compliance, AWS technology and services, billing, pricing, and support. It validates broad AWS Cloud knowledge rather than role-specific implementation skills.

• AWS Certified AI Practitioner covers AI and machine learning fundamentals, generative AI, foundation model applications, responsible AI, and security, compliance, and governance for AI solutions. It includes AWS services such as Amazon Bedrock, Amazon SageMaker AI, Amazon EC2, Amazon S3, and AWS Lambda.

No formal prerequisite is required, but candidates benefit from basic familiarity with cloud computing, AWS core services, and the AWS shared responsibility model.

AWS Associate Certifications cover role-based AWS skills for professionals who design, build, operate, and manage workloads in AWS environments.

Common Associate paths include

AWS Certified Solutions Architect Associate

AWS Certified Developer Associate

AWS Certified Data Engineer Associate

AWS Certified Machine Learning Engineer Associate

AWS Certified CloudOps Engineer Associate

• Architecture: designing secure, resilient, high-performing, and cost-aware solutions using AWS services and the AWS Well-Architected Framework.

• Development: building, testing, deploying, and troubleshooting cloud applications, including CI/CD workflows.

• Operations: monitoring workloads, managing access, applying networking concepts, handling continuity tasks, and improving cost and performance.

• Data and machine learning: building data pipelines, managing data quality, using Amazon SageMaker, and operating ML workloads on AWS.

No formal prerequisite is required, but candidates should have basic IT knowledge and hands-on AWS practice before attempting an Associate exam.

AWS Professional Certifications cover advanced AWS skills for senior practitioners who design, build, operate, automate, or manage production cloud systems.

Key competency areas include:

• Architecture: complex workload design, multi-account strategy, reliability, security, cost control, migration planning, and use of the AWS Well-Architected Framework.

• DevOps: CI/CD, infrastructure as code, monitoring, logging, incident response, configuration management, and automated deployment on AWS.

• Generative AI: foundation model integration, Amazon Bedrock, Retrieval Augmented Generation, vector stores, prompt engineering, agentic AI, safety, governance, testing, and operational tuning.

No specific prior AWS certification is required, but candidates should have substantial hands-on AWS experience before attempting a Professional exam.

AWS Specialty Certifications focus on deep technical skill in a specific AWS domain.

• Advanced Networking: network design, implementation, management, operations, and network security for AWS and hybrid environments. Candidates should understand services and concepts such as Amazon VPC, AWS Direct Connect, AWS Transit Gateway, routing, DNS, network automation, monitoring, encryption in transit, and multi-account networking.

• Security: detection, incident response, infrastructure security, identity and access management, data protection, security governance, and compliance. Candidates should be familiar with AWS IAM, AWS Organizations, AWS CloudTrail, Amazon GuardDuty, AWS Security Hub, AWS KMS, AWS WAF, and related security controls.

No formal prerequisite is required, but AWS recommends significant hands-on experience in the relevant specialty area before attempting these exams.