TRAINING AND CERTIFICATION
Plan your AWS
Certification Journey
Which AWS Certification should I start with?
New to IT and Cloud
From a non-IT background, switching to a cloud career?
Start with: AWS Certified Cloud Practitioner to validate foundational AWS Cloud knowledge, then earn AWS Certified AI Practitioner to showcase AI knowledge.
Outcome: Sharpens your competitive edge. Positions you for in-demand cloud and AI job roles and to earn additional AWS Certifications.
Line-of-Business Roles
In sales/marketing or other business roles?
Start with: AWS Certified Cloud Practitioner to validate foundational AWS Cloud knowledge, then earn AWS Certified AI Practitioner to showcase AI knowledge.
Outcome: Sharpens your competitive edge with in-demand AI and cloud knowledge and positions you for career advancement and higher pay
IT Professionals
Do you have 1-3 years of IT or STEM background?
Start with: An Associate-level AWS Certification that aligns with your role. AWS Certified AI Practitioner is recommended to validate conceptual AI knowledge.
Outcome: Boosts your confidence and credibility in contributing to AI and machine learning projects. Sets you up for career advancement, higher pay, and to earn advanced AWS Certifications.
AWS Certification Paths
Below are top cloud job roles, role responsibilities, and AWS Certification Paths aligned with those roles. Select the role(s) you are interested in and get started or continue your AWS Certification journey to achieve your career goals. Note: You are not required to follow these paths. These are recommended pathways. AWS Certified Cloud Practitioner is an optional step for candidates with an IT or STEM background. AWS Certified AI Practitioner is recommended for IT and non-IT professionals looking to leverage AI.
| Roles and responsibilities | AWS Certification Paths |
|---|---|
| Architecture | |
Solutions ArchitectDesign, develop, and manage cloud infrastructure and assets, work with DevOps to migrate applications to the cloud. |
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Application ArchitectDesign significant aspects of application architecture including user interface, middleware, and infrastructure, and ensure enterprise-wide scalable, reliable, and manageable systems. |
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| Data Analytics | |
Cloud Data EngineerAutomate collection and processing of structured/semi-structured data and monitor data pipeline performance. |
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| Development | |
Software Development EngineerDevelop, construct, and maintain software across platforms and devices. |
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| Operations | |
Systems AdministratorInstall, upgrade, and maintain computer components and software, and integrate automation processes. |
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Cloud EngineerImplement and operate an organization’s networked computing infrastructure and Implement security systems to maintain data safety. |
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| DevOps | |
Test EngineerEmbed testing and quality best practices for software development from design to release, throughout the product life cycle. |
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Cloud DevOps EngineerDesign, deployment, and operations of large-scale global hybrid cloud computing environment, advocating for end-to-end automated CI/CD DevOps pipelines. |
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DevSecOps EngineerAccelerate enterprise cloud adoption while enabling rapid and stable delivery of capabilities using CI/CD principles, methodologies, and technologies |
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| Security | |
Cloud Security EngineerDesign computer security architecture and develop detailed cyber security designs. Develop, execute, and trackperformance of security measures to protect information. |
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Cloud Security ArchitectDesign and implement enterprise cloud solutions applying governance to identify, communicate, and minimize business and technical risks. |
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| Networking | |
Network EngineerDesign and implement computer and information networks, such as local area networks (LAN), wide area networks (WAN), intranets, extranets, etc. |
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| Artificial Intelligence & Machine Learning | |
Prompt EngineerDesign, test, and refine text prompts to optimize the performance of AI language models. |
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Machine Learning EngineerResearch, build, and design artificial intelligence (AI) systems to automate predictive models, and design machine learning systems, models, and schemes. |
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Machine Learning Ops EngineerBuild and maintain AI and ML platforms and infrastructure. Design, implement, and operationally support AI/ML model activity and deployment infrastructure. |
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Data scientistDevelop and implement AI/ML models to solve business problems. Train and fine tune models and evaluate their performance. |
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