CREDENTIAL COMPARISON
Generative AI Certifications: Which Credential Fits Your Goal?
'GenAI certification' can mean a vendor exam, a course-completion certificate or a learning badge. These assess different things. Choose according to the knowledge or work you need to demonstrate, then check the current issuer requirements and whether practical project evidence is also needed.
Generative AI certifications fall into four categories: vendor certification exams (like AWS or Microsoft), course-completion certificates (awarded by training providers), learning badges (from short courses or modules), and portfolio evidence (your actual built systems). They assess different things and serve different goals. Choose based on what you need to demonstrate — a named credential for a job requirement, broad knowledge for literacy, or practical evidence for engineering ability. Always check the current issuer requirements before paying.
What kind of credential are you comparing?
These credential types assess different things and serve different goals.
| Credential type | What it may demonstrate | How it is assessed | What it does not automatically prove |
|---|---|---|---|
| Course-completion certificate | Completion of a structured programme's requirements | Coursework, projects and capstone reviewed by the provider | Vendor authorisation, university accreditation or employer recognition |
| Vendor certification exam | Knowledge of a specific platform's GenAI services and best practices | Proctored exam, often multiple choice plus practical components | Ability to build production GenAI systems without further practice |
| Learning badge | Completion of a short module or course | Quizzes, labs or attendance verification | Engineering depth or project-level capability |
| Portfolio evidence | Practical ability to define, build and evaluate GenAI systems | Inspectable code, evaluation results, failure analysis and design decisions | A standardised credential that passes automated screening |
Current options and who they suit
The following certifications are relevant to Generative AI as of September 2026. Verify current status, pricing and requirements on the official issuer pages before registering — exam details change frequently.
AWS Certified AI Practitioner: A foundational-level certification covering AI, ML and generative AI concepts, AWS services and responsible AI practices. Suitable for anyone working with AWS AI services. Assessment: proctored exam. Official source: aws.amazon.com/certification. Verify current status and pricing on the official page.
Microsoft Certified: Azure AI Fundamentals (AI-900): Covers AI workloads on Azure including generative AI services. Suitable for those working with Azure AI. Assessment: proctored exam. Official source: learn.microsoft.com. Verify current status.
Google Cloud Generative AI Learning Path: A learning path with badges for completing modules on Generative AI on Google Cloud. Suitable for Google Cloud users. Assessment: module completion and quizzes. Official source: cloud.google.com. Verify current offerings.
NVIDIA Deep Learning Institute: Offers courses and certificates in accelerated computing and AI, including LLM-related content. Suitable for engineers working with GPU acceleration. Official source: developer.nvidia.com. Verify current offerings.
This is not an exhaustive list. Other providers offer GenAI-related credentials. If an exam is retired, do not recommend taking it — check whether a successor is officially stated.
Choose by your goal
For cloud-specific responsibilities: if your role requires working with a specific cloud provider's AI services, the vendor's foundational or associate certification is the relevant choice. Check which exam covers GenAI services specifically.
For general AI literacy: if you need to understand GenAI concepts for management, product or non-engineering roles, a foundational vendor exam or a structured course with a completion certificate may suffice.
For engineering skill development: if your goal is to build and evaluate GenAI systems, a course with project reviews and evaluation evidence is more relevant than a multiple-choice exam. Portfolio evidence — actual built systems with documented evaluation — demonstrates this capability more concretely than any certificate.
For a role explicitly requiring a named credential: if a job posting requires a specific certification, that certification is the one to pursue. No course certificate substitutes for a required vendor exam.
Does a certificate show that you can build a GenAI system?
A certificate shows that you met the requirements set by the issuer. What those requirements actually test varies. A multiple-choice exam tests knowledge recall and conceptual understanding. A course with project reviews tests whether your systems pass evaluation. Portfolio evidence — a GitHub repository with a README, evaluation script, test cases and failure analysis — shows what you can actually build.
Practical evidence adds: problem definition (what the system does), data decisions (what data is used and why), baseline (what a simpler approach achieves), tests (specific cases with expected outcomes), failed examples (where the system breaks), and revisions (what you changed and why). These are not assessed by most certification exams. Link to the projects guide for what practical evidence looks like in detail.
What SCAI's completion certificate represents
School of Core AI awards a course-completion certificate to learners who complete the Generative AI course requirements — including the guided projects and capstone. The certificate is issued by School of Core AI. It represents completion of the programme's project and assessment requirements.
SCAI does not award any external vendor certification (AWS, Microsoft, Google, NVIDIA). SCAI's certificate is not a university degree, government licence or vendor-authorised credential. The certificate does not guarantee employment, salary or employer recognition. The practical project evidence — the systems you build and evaluate during the course — is typically more meaningful to technical interviewers than the certificate itself.
For the syllabus, project expectations and completion-certificate details, review SCAI's live Generative AI course.
What to verify before paying
Before paying for any GenAI certification or course: check exam versus tuition cost — a vendor exam fee is separate from course tuition. Check current credential status — is the exam active or retired? Check recommended experience — do you meet the prerequisites? Check assessment method — is it multiple choice, practical or project-based? Check retake and renewal terms — what happens if you fail, and does the credential expire? Check whether an exam voucher is included — some courses include a voucher, most do not.
For SCAI's fee and inclusions, confirm the total payable amount including applicable taxes before enrolling. See the fees comparison guide for a structured approach to evaluating course costs.