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Test your knowledge of how to assess business and technical requirements, select the appropriate foundation models, and configure models effectively to meet performance, cost, security, and scalability goals.

Test your knowledge of implementing data validation and processing pipelines for foundation model consumption, and designing and implementing vector store solutions to enable efficient retrieval, grounding, and scalable generative AI applications.

Test your knowledge of designing retrieval mechanisms to augment foundation models, and implementing prompt engineering strategies and governance to ensure safe, reliable, and consistent foundation model interactions.

Test your knowledge of implementing foundation model deployment strategies and enterprise integration architectures! Including deploying foundation models based on application and performance needs, addressing large language model deployment challenges, optimizing performance and resource usage, integrating generative AI into existing enterprise systems, designing secure and compliant access frameworks, enabling cross-environment and hybrid deployments, and implementing CI/CD pipelines and GenAI gateway architectures for scalable, secure, and controlled enterprise adoption.

Test your knowledge of implementing input and output safety controls, and enforcing data security and privacy measures to protect users, data, and generative AI systems.