The open specification for connecting AI applications to external tools, data sources, prompts, and interactive apps.
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Risks and mitigations for developing and deploying generative AI applications.
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Code examples for structured outputs, tool use, retrieval, evals, and other LLM application patterns.
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OpenAI's guide to models, tools, instructions, orchestration, and guardrails.
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Anthropic's practical patterns and tradeoffs for agentic systems.
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An open course on designing, developing, deploying, and iterating on production ML systems.
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Focused courses on current generative AI engineering techniques.
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An introductory path through generative AI concepts and Google Cloud tooling.
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Deep learning foundations and applications.
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Build language models from data preparation through evaluation and deployment.
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A code-first introduction to deep learning.
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The full lifecycle of building and shipping AI products.
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