There is a wide variety of certifications for the three major clouds. The path that each person should follow to become certified in one or another cloud depends on many factors, such as interest, need, economic viability and professional field.
We have developed lists with all the possible certifications to date in each cloud (with the exception of Azure, which has many more available, we only limit ourselves to those related to the world of Data). It must be taken into account that certifications are constantly modified, so it is always advisable to verify at the moment which ones are available and look for updated sources for preparing them.
Certifications for Amazon Web Service
https://aws.amazon.com/certification/
Keep in mind that some certifications are new and that is why they are not in the graph.
🎓 AWS Certified Cloud Practitioner –
This certification validates basic knowledge of the AWS cloud.
- Previous experience – No previous AWS experience is required.
- Previous certifications required – None
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Solutions Architect – Associate –
This certification demonstrates your knowledge and skills in AWS and builds your credibility as an AWS cloud professional.
- Previous Experience – Strong prior experience in on-premises or cloud IT is recommended.
- Previous certifications required – None
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Solutions Architect – Professional –
This certification validates advanced skills and knowledge needed to design secure, optimized, and modern applications and automate processes on AWS.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Previous certifications required – AWS Certified Solutions Architect – Associate.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified SysOps Administrator – Associate –
This certification validates your technical skills in implementation, administration and operations on the AWS platform.
- Previous Experience – Strong prior experience in on-premises or cloud IT is recommended.
- Previous certifications required – None
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified DevOps Engineer – Professional –
This certification validates your technical skills in provisioning, operating, and managing distributed applications on the AWS platform.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Previous certifications required – AWS Certified Developer – Associate or AWS Certified SysOps Administrator – Associate.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Advanced Networking – Specialty –
This certification validates your advanced technical skills in designing and implementing AWS network services.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Developer – Associate –
This certification validates your technical skills in developing and maintaining applications on the AWS platform.
- Previous Experience – Strong prior experience in on-premises or cloud IT is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Data Analytics – Specialty –
This certification validates your technical skills in designing and implementing AWS data analytics services.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Database – Specialty –
This certification validates your technical skills in designing and implementing AWS database services.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Machine Learning – Specialty –
This certification validates your technical skills in designing and implementing AWS machine learning services.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Security – Specialty –
This certification validates your technical skills in designing and implementing AWS security services.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified SAP on AWS – Specialty –
This certification validates your technical skills in SAP system design and implementation on AWS.
- Previous experience – 2 years of previous AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Alexa Skill Builder – Specialty –
This certification validates your ability to build, test, and publish Amazon Alexa applications.
- Previous experience – 6 months of hands-on experience designing and building Alexa apps is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified IoT – Specialty –
This certification validates your ability to design and implement AWS solutions for the Internet of Things (IoT).
- Previous experience – 2 years of AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Big Data – Specialty –
This certification validates your ability to design and implement big data solutions using tools and services on the AWS platform.
- Previous experience – 2 years of AWS cloud experience is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AWS Certified Data Engineer – Associate –
Associate validates skills and knowledge in key data-related AWS services, the ability to implement data pipelines, monitor and troubleshoot, and optimize costs and performance according to best practices. Available from October 31.
- Previous Experience – Strong prior experience in on-premises or cloud IT is recommended.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
Certifications for Microsoft Azure linked to Data
https://learn.microsoft.com/credentials/
Keep in mind that some certifications are new and that is why they are not in the graph.
🎓 AZ-900 Certification – Azure Fundamentals –
The AZ-900 certification is a foundational certification that provides an overview of the basics of Microsoft Azure. It covers topics such as cloud infrastructure, core Azure services, security and compliance, and Azure billing and support.
- Previous experience – No prior Azure experience required.
- Previous certifications required – None
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 Microsoft Certified: Azure Data Fundamentals – DP-900 –
This certification is aimed at people interested in data management and analysis in the Azure cloud. It is relevant to roles such as data analysts, database developers, and other professionals who work with data and want to understand how Azure can be used to store and analyze data.
- Previous experience – No previous experience is required.
- Previous certifications required – None
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 AI-900 Certification – Azure AI Fundamentals –
The AI-900 certification is designed to provide a fundamental understanding of artificial intelligence concepts and services in Azure. It covers topics such as machine learning, natural language processing (NLP), and computer vision in Azure.
- Previous experience – No previous experience in AI or Azure is required.
- Previous certifications required – None
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
🎓 Microsoft Certified: Azure Data Engineer Associate – DP-203 –
This certification focuses on implementing and managing data engineering solutions in Azure. It is aimed at professionals who want to work in the design, implementation and administration of data processing and storage solutions in the Azure cloud. Typical roles include data engineers, ETL (Extract, Transform, Load) developers, data architects, and other professionals related to cloud data engineering.
- Previous experience – Previous experience implementing data analytics solutions in Azure is recommended.
- Previous Certifications Required – No prior certifications are required, but the Azure Fundamentals certification is helpful as preparation.
- Hours of investment – May require around 40-60 hours of study and practical experience.
🎓 Microsoft Certified: Azure AI Engineer Associate – AI-102 –
The Azure AI Engineer Associate certificate focuses on implementing Artificial Intelligence (AI) and Machine Learning (ML) solutions in Azure. It is relevant for AI and ML engineers, AI developers, and professionals working on AI projects in Azure.
- Previous experience – Previous experience implementing Artificial Intelligence (AI) and Machine Learning (ML) solutions in Azure is recommended.
- Previous Certifications Required – No prior certifications are required, but the Azure Fundamentals certification is helpful as preparation.
- Hours of investment – May require around 40-60 hours of study and practical experience.
🎓 Microsoft Certified: Azure Database Administrator Associate – DP-300 –
This certification is aimed at database administrators who work with database solutions in Azure. It focuses on the implementation, management and optimization of databases in the Azure cloud.
- Previous experience – Previous experience in general database administration is recommended.
- Previous Certifications Required – No prior certifications are required, but the Azure Fundamentals certification is helpful as preparation.
- Hours of investment – May require around 40-60 hours of study and practical experience.
🎓 Microsoft Certified: Azure AI Data Scientist Associate – DP-100 –
This certification validates skills in building machine learning solutions in Azure. It is aimed at professionals who want to work as data scientists and developers of Machine Learning models on Microsoft’s cloud platform, Azure.
- Previous experience – Previous experience building machine learning solutions is recommended.
- Previous Certifications Required – No prior certifications are required, but the Azure Fundamentals certification is helpful as preparation.
- Hours of investment – May require around 40-60 hours of study and practical experience.
Azure Externals’
🎓 Microsoft Certified: Power BI Fundamentals – PL-900 –
The Power BI Fundamentals certification focuses on the Power BI data visualization tool. It is aimed at people who want to understand how to use Power BI to create interactive reports and dashboards. It is relevant to roles such as data analysts, BI professionals and report developers.
- Previous experience – No previous experience is required.
- Required prior certifications – None.
- Hours of investment – Varies depending on experience, but generally takes around 16-32 hours of study.
Google Cloud Platform Certifications
https://cloud.google.com/learn/certification
Keep in mind that some certifications are new and that is why they are not in the graph.
🎓 Foundational Certification –
Validates your extensive knowledge of cloud concepts and Google Cloud products, services, tools, features, benefits, and use cases.
- Recommended experience – Collaborative role with technical professionals. No technical prerequisites.
- Registration fee – USD$99
Cloud Digital Leader:
A Cloud Digital Leader in the cloud can fluidly monitor the capabilities of Google Cloud’s core products and services and how they benefit organizations.
This certification is for anyone who wants to expand their knowledge of the basics of cloud computing and how Google Cloud products and services can be used to achieve an organization’s goals.
🎓 Associate Certification –
Gain the foundational skills to implement cloud projects with a path to professional certification.
- Recommended experience – More than 6 months building on Google Cloud.
- Registration fee – USD$125 (plus taxes where applicable)
Associate Cloud Engineer:
Associate Cloud Engineers deploy applications, manage business solutions, and monitor operations. They use the Google Cloud Console and the command line interface to perform common platform-based tasks to maintain deployed solutions that leverage self-managed or Google-managed services on Google Cloud.
🎓 Professional Certification –
Assess key technical job functions, advanced and fluent skills in Google Cloud implementation, design and product management.
Associate Cloud Engineers deploy applications, manage business solutions, and monitor operations. They use the Google Cloud Console and the command line interface to perform common platform-based tasks to maintain deployed solutions that leverage self-managed or Google-managed services on Google Cloud.
- Recommended experience – 3+ years of experience in the cloud industry, and at least 1 year working with Google Cloud.
- Registration fee – USD$200 (plus taxes where applicable)
Professional Cloud Architect:
Professional Cloud Architects enable organizations to leverage Google Cloud technologies. With a comprehensive understanding of cloud architecture and Google Cloud, they develop, design, and manage robust, scalable, secure, highly available, and dynamic solutions to drive business objectives.
Professional Cloud Database Engineer BETA:
A Professional Cloud Database Engineer BETA is a database professional who has two years of experience in Google Cloud and five years of general database and IT experience. The Professional Cloud Database Engineer creates, designs, manages, and troubleshoots Google Cloud databases used by applications to store and retrieve data. The professional cloud database engineer should be able to comfortably deal with translating technical and business requirements into scalable and cost-effective database solutions.
Professional Cloud Developer:
Professional Cloud Developers create highly available, scalable applications using Google-recommended practices and tools. They have experience with cloud-native applications, managed services, developer tools, and next-generation databases. Cloud developers also master at least one general-purpose programming language and are trained to produce meaningful metrics as well as logs for debugging and tracing code.
Professional Data Engineer:
A Professional Data Engineer enables data-driven decision making by collecting, transforming and publishing it. A data engineer must be able to build, design, operationalize, secure and monitor data processing systems with a particular focus on security and compliance; reliability and fidelity; scalability and efficiency; and flexibility and portability. A data engineer should also be able to continuously use, deploy, and train pre-existing machine learning models.
Professional Cloud DevOps Engineer:
A Professional Cloud DevOps Engineer carries out efficient development operations that can balance delivery speed and service reliability. They have experience using Google Cloud to create software delivery pipelines, deploy and monitor services, and manage and learn from incidents.
Professional Cloud Security Engineer:
A Professional Cloud Security Engineer enables organizations to design and deploy secure infrastructure and workloads on Google Cloud. With a good understanding of industry security requirements, they design, develop and manage a secure infrastructure using Google security technologies. The cloud security engineer must be proficient in all aspects of cloud security, including identity and access management, using Google technologies to provide data protection, defining policies and organizational structures, configuring network security defenses, managing incident responses, collecting and analyzing Google Cloud logs.
Professional Cloud Network Engineer:
A Professional Cloud Network Engineer manages network architectures on Google Cloud. Work on networking or cloud teams with architects who design cloud infrastructure. They use the Google Cloud Console and/or the command line interface, and leverage experience with network services, hybrid and multi-cloud connectivity, application and container networking, VPC deployment, and security for network architectures to ensure successful deployments across Cloud.
Professional Collaboration Engineer:
A Professional Collaboration Engineer transforms business objectives into tangible security configurations, practices and policies related to users, content and integrations. By understanding your organization’s infrastructure, collaboration engineers enable people to work together, access data, and communicate securely and efficiently. They use tools, programming languages, and APIs to automate workflows. They look for opportunities to educate end users and increase operational efficiency while advocating for Google Workspace.
Professional Machine Learning Engineer:
Professional Machine Learning Engineer creates and produces machine learning models to solve business challenges using Google Cloud technologies and knowledge of machine learning models and techniques. The ML Engineer holds AI accountable throughout the ML development process and collaborates with other job roles to ensure the long-term success of the models. The ML engineer must be proficient in all aspects of model architecture, metric interpretation, and data pipeline interaction. The ML engineer needs to be familiar with concepts of application development, infrastructure management, data governance, and data engineering. By understanding training, deployment, retraining, model enhancement, and scheduling, ML engineer monitoring creates scalable solutions for optimal performance.
Comparison Table between Microsoft Azure, Amazon Web Service and Google Cloud Platform
Conclusion
There are many options for obtaining certifications in the three most popular clouds. It is important to always stay up to date with the new certifications available, as these are constantly changing according to personal and professional needs. To properly prepare for each exam, it is advisable to have access to the selected cloud and accumulate experience in it as much as possible.
Likewise, there are a large number of resources available on platforms such as Udemy, YouTube, and especially official websites. It is always advisable to verify that the selected materials are up to date.
👨💻 Study material on Official sites
On these sites there is a lot of valuable information, such as study paths aimed especially at each certification, test exams, as well as access to schedule the exam dates or consult any questions related to the certifications and exam modality:
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