AWS AIP-C01 Practice Exam: Cost & Performance Optimization (Domain 4) - Part 13 of 20 скачать в хорошем качестве

AWS AIP-C01 Practice Exam: Cost & Performance Optimization (Domain 4) - Part 13 of 20

This AIP-C01 practice exam targets Domain 4, testing your ability to optimize GenAI applications for cost, performance, and scalability. Practice exam topics: • Performance and latency optimization • Cost control and usage monitoring • Scaling GenAI workloads • Operational best practices Ideal for architects and operators preparing for AIP-C01. #AWSAIP #AWSAIPC01 #GenAIOps #AIOptimization #CloudAI #AWSExamPrep #CostOptimization #PerformanceTuning #AIPC01Practice #AIPractitioner #AWSCertification #ArtificialIntelligence #GenAIScaling TIMESTAMP 0:00 - Disclaimer 0:14 - Session Format 0:35 - What to Expect 0:44 - Exam + Domain Scope 0:55 - Q1-Time-to-First-Token Optimization for Frequent System Prompts 1:23 - Q2-Llama 3 Memory Reduction via Quantization and PEFT 1:51 - Q3-Elastic Traffic Handling with Bedrock Auto-Scaling 2:19 - Q4-RAG Context Pruning to Reduce Token Costs 2:47 - Q5-Parameter-Efficient Fine-Tuning for Titan Image Generator 3:15 - Q6-Multi-Region Traffic Routing for Throttle Management 3:43 - Q7-Batch Execution Mode for Non-Real-Time GenAI Tasks 4:11 - Q8-Mixtral Endpoint Throughput Optimization with xFormers 4:39 - Q9-KV Cache Management for Long-Form Generation Stability 5:07 - Q10-Speed Evaluation Metric for First-Token Latency 5:35 - Q11-Impact of Bedrock Guardrails on Operational Efficiency 6:03 - Q12-Embedding Storage Optimization in RAG Pipelines 6:31 - Q13-SageMaker Deployment Configuration for Max GPU Utilization 6:59 - Q14-Monitoring Bedrock API Health with CloudWatch Metrics 7:27 - Q15-Optimizing Low-Latency Chatbots with Smaller Models 7:55 - Q16-Cost and Performance Check for Long Legal Document Summaries 8:23 - Q17-Operational Bias and Fairness Monitoring with SageMaker Clarify 8:51 - Q18-Provisioned Throughput for Dedicated Bedrock Model Capacity 9:19 - Q19-Small-to-Big Retrieval Optimization in RAG Systems 9:47 - Q20-Cost Reduction in High-Resolution Image Generation 10:15 - Q21-Benefits of Bedrock Model Copy Across Regions 10:43 - Q22-Semantic Caching Placement for AWS GenAI Applications 11:11 - Q23-Tensor Parallelism Role in SageMaker LMI Containers 11:39 - Q24-Chunking Strategy Optimization for Knowledge Base Retrieval 12:10 - Q25-Multi-Region Bedrock Deployment for High Availability 12:38 - Playlist + PDF Access