[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"cheat-sheet---en":3,"domain-info---en":3,"topic-info----en":3,"next-aws-certified-ai-practitioner-genai-fundamentals-genai-core-concepts-the-foundation-model-lifecycle-en":4,"prev-aws-certified-ai-practitioner-genai-fundamentals-genai-core-concepts-the-foundation-model-lifecycle-en":18,"lesson-aws-certified-ai-practitioner-genai-fundamentals-genai-core-concepts-the-foundation-model-lifecycle-en":29},null,{"locked":5,"reason":6,"meta":7,"item":3},true,"paywall",{"title":8,"description":9,"isFree":10,"estimatedMinutes":11,"difficulty":12,"learningObjectives":13},"Token-Based Pricing","Learn how generative AI bills, why output tokens cost more than input tokens, and how on-demand, batch, Provisioned Throughput, and prompt caching change the cost of the same workload.",false,20,"intermediate",[14,15,16,17],"Explain how token-based pricing works and why input and output tokens are priced differently","Estimate the monthly cost of a workload from its token volumes","Compare on-demand, batch, and Provisioned Throughput and identify which fits a given scenario","Describe how prompt caching reduces cost and what its limitations are",{"locked":5,"reason":6,"meta":19,"item":3},{"title":20,"description":21,"isFree":10,"estimatedMinutes":22,"difficulty":23,"learningObjectives":24},"Generative AI Use Cases","Work through the use cases the exam names, grouped by the capability behind them: generating new content, transforming existing content, holding a conversation, and finding what matters.",16,"beginner",[25,26,27,28],"Identify the generative AI use cases named in the exam guide and the capability each one draws on","Distinguish an AI assistant from a customer service agent and search from recommendation","Explain why summarization and translation carry lower risk than open-ended generation","Judge from a scenario whether generative AI is the right fit or traditional ML is a better answer",{"locked":5,"reason":6,"meta":30,"item":3},{"title":31,"description":32,"isFree":10,"estimatedMinutes":33,"difficulty":12,"learningObjectives":34},"The Foundation Model Lifecycle","Walk the seven stages the exam names, from data selection to feedback, and see why model selection replaces training as the decision that matters most when you build on a foundation model.",18,[35,36,37,38],"List the stages of the FM lifecycle named in the exam guide and describe what happens in each","Distinguish pre-training from fine-tuning by data, cost, and who performs it","Explain why model selection carries more weight in the FM lifecycle than in a traditional ML pipeline","Describe how the feedback stage closes the loop and what it feeds"]