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Choosing AI tools: vendor landscape + cert tracks
In this lesson
Choosing AI tools: vendor landscape + cert tracks
Map the major generative AI vendors (Anthropic, OpenAI, Google, AWS, NVIDIA, Microsoft) to their primary service offerings and infrastructure strengths, distinguishing between mode
You'll be able to
- Map the major generative AI vendors (Anthropic, OpenAI, Google, AWS, NVIDIA, Microsoft) to their primary service offerings and infrastructure strengths, distinguishing between model providers, platform operators, and hardware accelerators based on official vendor documentation [^1][^2].
- Classify vendor-specific tooling and APIs (for example, Vertex AI Studio, Amazon Bedrock endpoints, NVIDIA NIM microservices) according to the work patterns they support, such as grounding with enterprise data, agent orchestration, or low-code model deployment [^1][^3][^4].
- Evaluate certification pathways across AWS Certified AI Practitioner (AIF-C01), Google Cloud Generative AI Leader, and NVIDIA generative AI certifications by identifying which exam domains address vendor landscape knowledge, governance requirements, and platform-specific services [^1][^6].
- Apply exam-aligned decision criteria to select appropriate cloud services and compliance tools (for example, AWS Artifact, CloudTrail, Trusted Advisor; Google Cloud governance frameworks; NVIDIA accelerated infrastructure) for production AI solutions that meet regulatory and operational requirements [^1][^6].