| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 01. Analyze Requirements and Design GenAI Solutions | |||
| 01 | |||
| 02. Select and Configure FMs | |||
| 01. Overview of Foundation Models Available in Amazon Bedrock.mp4 | 9.1 MB | ||
| 01. Overview of Foundation Models Available in Amazon Bedrock.srt | 5.5 KB | ||
| 02 | |||
| 03. Implement Data Validation and Processing Pipelines for FM Consumption | |||
| 01. Why Data Pipelines Matter for Generative AI Systems.mp4 | 7.9 MB | ||
| 01. Why Data Pipelines Matter for Generative AI Systems.srt | 4.9 KB | ||
| 02. Data Requirements for Foundation Model Inference.mp4 | 11.3 MB | ||
| 02. Data Requirements for Foundation Model Inference.srt | 6.4 KB | ||
| 03 | |||
| 04. Design and Implement Vector Store Solutions | |||
| 01. What Are Vector Stores.mp4 | 12.4 MB | ||
| 01. What Are Vector Stores.srt | 6.8 KB | ||
| 02. Understanding Embeddings.mp4 | 4.7 MB | ||
| 02. Understanding Embeddings.srt | 3.4 KB | ||
| 03. Embeddings Models in Amazon Bedrock.mp4 | 7.9 MB | ||
| 03. Embeddings Models in Amazon Bedrock.srt | 4.5 KB | ||
| 04 | |||
| 05. Design Retrieval Mechanisms for FM Augmentation | |||
| 01. How Retrieval Augmented Generation Works.mp4 | 8.7 MB | ||
| 01. How Retrieval Augmented Generation Works.srt | 5.9 KB | ||
| 02. Designing Effective Document Chunking Strategies.mp4 | 15.6 MB | ||
| 02. Designing Effective Document Chunking Strategies.srt | 8.4 KB | ||
| 03. Selecting Embedding Models or Retrieval Systems.mp4 | 10.6 MB | ||
| 03. Selecting Embedding Models or Retrieval Systems.srt | 6 KB | ||
| 04. Deploying Vector Search Systems.mp4 | 11.7 MB | ||
| 04. Deploying Vector Search Systems.srt | 8 KB | ||
| 05 | |||
| 06. Implement Prompt Engineering Strategies and Governance for FM Interactions | |||
| 01. Why Prompt Engineering Matters.mp4 | 10.2 MB | ||
| 01. Why Prompt Engineering Matters.srt | 6.3 KB | ||
| 02. Designing Effective Prompt Instructions.mp4 | 5.7 MB | ||
| 02. Designing Effective Prompt Instructions.srt | 4.2 KB | ||
| 03. Demo Creating Prompt Templates with Amazon Bedrock Prompt Management.mp4 | 14.9 MB | ||
| 03. Demo Creating Prompt Templates with Amazon Bedrock Prompt Management.srt | 4.7 KB | ||
| 04. Using Guardrails to Control Model Behavior.mp4 | 10.9 MB | ||
| 04. Using Guardrails to Control Model Behavior.srt | 8.6 KB | ||
| 05. Demo Using Bedrock Guardrails to Block Restricted Content.mp4 | 17.9 MB | ||
| 05. Demo Using Bedrock Guardrails to Block Restricted Content.srt | 6.5 KB | ||
| 06 | |||
| demos.txt | 307.2 B | ||
| implement-prompt-engineering-strategies-and-governance-for-fm-interactions-slides.pdf | 10.7 MB | ||
| 06. Designing Conversational AI Systems.mp4 | 16.2 MB | ||
| 06. Designing Conversational AI Systems.srt | 11.1 KB | ||
| 07. Demo Maintaining Conversation History with DynamoDB.mp4 | 12.3 MB | ||
| 07. Demo Maintaining Conversation History with DynamoDB.srt | 4.8 KB | ||
| 08. Prompt Governance and Lifecycle Management.mp4 | 16.2 MB | ||
| 08. Prompt Governance and Lifecycle Management.srt | 10.2 KB | ||
| 09. Monitoring Prompt Performance.mp4 | 15 MB | ||
| 09. Monitoring Prompt Performance.srt | 10 KB | ||
| 10. Prompt Optimization Techniques.mp4 | 12.6 MB | ||
| 10. Prompt Optimization Techniques.srt | 8.4 KB | ||
| 11. Designing Multi Step Prompt Workflows on AWS.mp4 | 10 MB | ||
| 11. Designing Multi Step Prompt Workflows on AWS.srt | 7.6 KB | ||
| 12. Demo Creating a Prompt Flow in Amazon Bedrock.mp4 | 18.4 MB | ||
| 12. Demo Creating a Prompt Flow in Amazon Bedrock.srt | 5.5 KB | ||
| 13. Common Prompt Engineering Issues.mp4 | 9.3 MB | ||
| 13. Common Prompt Engineering Issues.srt | 6 KB | ||
| 14. Module Summary Part 1.mp4 | 9.4 MB | ||
| 14. Module Summary Part 1.srt | 6 KB | ||
| 15. Module Summary Part 2.mp4 | 8.1 MB | ||
| 15. Module Summary Part 2.srt | 5.3 KB | ||
| 16. Sample Question.mp4 | 18.7 MB | ||
| 16. Sample Question.srt | 7.5 KB | ||
| demos.txt | 307.2 B | ||
| design-retrieval-mechanisms-for-fm-augmentation-slides.pdf | 28.4 MB | ||
| 05. Demo Performing Vector Similarity Search.mp4 | 15.1 MB | ||
| 05. Demo Performing Vector Similarity Search.srt | 5.6 KB | ||
| 06. Demo Implementing Hybrid Search.mp4 | 16.8 MB | ||
| 06. Demo Implementing Hybrid Search.srt | 4.4 KB | ||
| 07. Improving Retrieval with Bedrock Reranking Models.mp4 | 10.5 MB | ||
| 07. Improving Retrieval with Bedrock Reranking Models.srt | 6.3 KB | ||
| 08. Query Expansion and Decomposition Techniques.mp4 | 11.6 MB | ||
| 08. Query Expansion and Decomposition Techniques.srt | 6.5 KB | ||
| 09. Demo Implementing Query Expansion.mp4 | 6.5 MB | ||
| 09. Demo Implementing Query Expansion.srt | 2.2 KB | ||
| 10. Standardizing Retrieval Interfaces.mp4 | 19.6 MB | ||
| 10. Standardizing Retrieval Interfaces.srt | 12.4 KB | ||
| 11. Integrating Retrieval Systems with Foundation Models.mp4 | 8.4 MB | ||
| 11. Integrating Retrieval Systems with Foundation Models.srt | 4.9 KB | ||
| 12. Common Retrieval System Issues.mp4 | 7.3 MB | ||
| 12. Common Retrieval System Issues.srt | 5 KB | ||
| 13. Module Summary.mp4 | 12.6 MB | ||
| 13. Module Summary.srt | 7.9 KB | ||
| 14. Sample Question.mp4 | 19.5 MB | ||
| 14. Sample Question.srt | 7.2 KB | ||
| demos.txt | 307.2 B | ||
| design-and-implement-vector-store-solutions-slides.pdf | 26.4 MB | ||
| 04. Demo Generating Embeddings Using Amazon Bedrock.mp4 | 11.1 MB | ||
| 04. Demo Generating Embeddings Using Amazon Bedrock.srt | 3 KB | ||
| 05. Vector Databases Explained.mp4 | 3.7 MB | ||
| 05. Vector Databases Explained.srt | 2.4 KB | ||
| 06. Vector Storage on AWS.mp4 | 10.8 MB | ||
| 06. Vector Storage on AWS.srt | 7 KB | ||
| 07. Amazon Bedrock Knowledge Bases Overview.mp4 | 8.9 MB | ||
| 07. Amazon Bedrock Knowledge Bases Overview.srt | 5.6 KB | ||
| 08. Demo Creating a Bedrock Knowledge Base.mp4 | 25.4 MB | ||
| 08. Demo Creating a Bedrock Knowledge Base.srt | 8 KB | ||
| 09. Demo Adding Metadata to a Knowledge Base.mp4 | 12.2 MB | ||
| 09. Demo Adding Metadata to a Knowledge Base.srt | 4.3 KB | ||
| 10. Designing Metadata Frameworks for Vector Stores.mp4 | 10.2 MB | ||
| 10. Designing Metadata Frameworks for Vector Stores.srt | 6.6 KB | ||
| 11. High Performance Vector Search Architectures Part 1.mp4 | 13.8 MB | ||
| 11. High Performance Vector Search Architectures Part 1.srt | 8.8 KB | ||
| 12. High Performance Vector Search Architectures Part 2.mp4 | 9.8 MB | ||
| 12. High Performance Vector Search Architectures Part 2.srt | 7.4 KB | ||
| 13. Demo Creating a Vector Index in Amazon OpenSearch.mp4 | 21.6 MB | ||
| 13. Demo Creating a Vector Index in Amazon OpenSearch.srt | 6.5 KB | ||
| 14. Integrating Enterprise Data Sources.mp4 | 9 MB | ||
| 14. Integrating Enterprise Data Sources.srt | 4.7 KB | ||
| 15. Demo Ingesting Documents into a Vector Store.mp4 | 23.7 MB | ||
| 15. Demo Ingesting Documents into a Vector Store.srt | 7.7 KB | ||
| 16. Demo Automating Vector Store Updates.mp4 | 24.5 MB | ||
| 16. Demo Automating Vector Store Updates.srt | 8.4 KB | ||
| 17. Common Vector Store Issues.mp4 | 17.2 MB | ||
| 17. Common Vector Store Issues.srt | 11.4 KB | ||
| 18. Module Summary Part 1.mp4 | 10.6 MB | ||
| 18. Module Summary Part 1.srt | 6.8 KB | ||
| 19. Module Summary Part 2.mp4 | 8.5 MB | ||
| 19. Module Summary Part 2.srt | 6 KB | ||
| 20. Sample Exam Question.mp4 | 17 MB | ||
| 20. Sample Exam Question.srt | 7 KB | ||
| demos.txt | 307.2 B | ||
| implement-data-validation-and-processing-pipelines-for-fm-consumption-slides.pdf | 27 MB | ||
| 03. Designing Data Validation Workflows.mp4 | 8.5 MB | ||
| 03. Designing Data Validation Workflows.srt | 5.7 KB | ||
| 04. Demo Validating Data with AWS Glue Data Quality.mp4 | 18.3 MB | ||
| 04. Demo Validating Data with AWS Glue Data Quality.srt | 6.2 KB | ||
| 05. Preprocessing Unstructured Data for GenAI Applications.mp4 | 12.3 MB | ||
| 05. Preprocessing Unstructured Data for GenAI Applications.srt | 7.8 KB | ||
| 06. Processing Multimodal Data.mp4 | 13 MB | ||
| 06. Processing Multimodal Data.srt | 6.8 KB | ||
| 07. Demo Building a Multimodal Processing Pipeline.mp4 | 21.3 MB | ||
| 07. Demo Building a Multimodal Processing Pipeline.srt | 6.9 KB | ||
| 08. Formatting Data for Foundation Model Inference.mp4 | 13.8 MB | ||
| 08. Formatting Data for Foundation Model Inference.srt | 7.8 KB | ||
| 09. Demo Formatting Bedrock Inference Requests.mp4 | 5.4 MB | ||
| 09. Demo Formatting Bedrock Inference Requests.srt | 2 KB | ||
| 10. Enhancing Input Data Quality.mp4 | 10.4 MB | ||
| 10. Enhancing Input Data Quality.srt | 6.5 KB | ||
| 11. Using Entity Extraction for Data Enrichment.mp4 | 6.5 MB | ||
| 11. Using Entity Extraction for Data Enrichment.srt | 3.8 KB | ||
| 12. Demo Enhancing Data with Amazon Comprehend.mp4 | 7.3 MB | ||
| 12. Demo Enhancing Data with Amazon Comprehend.srt | 2.8 KB | ||
| 13. Designing Scalable Data Processing Pipelines.mp4 | 9.3 MB | ||
| 13. Designing Scalable Data Processing Pipelines.srt | 5.5 KB | ||
| 14. Using SageMaker Processing for Data Preparation.mp4 | 6.6 MB | ||
| 14. Using SageMaker Processing for Data Preparation.srt | 4.3 KB | ||
| 15. Demo Running a SageMaker Processing Job.mp4 | 26.6 MB | ||
| 15. Demo Running a SageMaker Processing Job.srt | 6.8 KB | ||
| 16. Monitoring Data Pipeline Quality.mp4 | 6.8 MB | ||
| 16. Monitoring Data Pipeline Quality.srt | 4.8 KB | ||
| 17. Common Data Pipeline Issues in GenAI Systems.mp4 | 13.5 MB | ||
| 17. Common Data Pipeline Issues in GenAI Systems.srt | 9.5 KB | ||
| 18. Module Summary Part 1.mp4 | 13.2 MB | ||
| 18. Module Summary Part 1.srt | 6.8 KB | ||
| 19. Module Summary Part 2.mp4 | 11.8 MB | ||
| 19. Module Summary Part 2.srt | 7.9 KB | ||
| 20. Sample Question.mp4 | 20 MB | ||
| 20. Sample Question.srt | 7.9 KB | ||
| demos.txt | 307.2 B | ||
| select-and-configure-fms-slides.pdf | 22.4 MB | ||
| 02. Designing Flexible Multi-model Architectures.mp4 | 8 MB | ||
| 02. Designing Flexible Multi-model Architectures.srt | 5.6 KB | ||
| 03. Demo Dynamic Model Selection.mp4 | 13.9 MB | ||
| 03. Demo Dynamic Model Selection.srt | 5.5 KB | ||
| 04. Designing Resilient GenAI Systems.mp4 | 5 MB | ||
| 04. Designing Resilient GenAI Systems.srt | 3.4 KB | ||
| 05. Cross-region Model Deployment Strategies.mp4 | 6.8 MB | ||
| 05. Cross-region Model Deployment Strategies.srt | 4.1 KB | ||
| 06. Demo Implementing a Model Failover Strategy.mp4 | 11.8 MB | ||
| 06. Demo Implementing a Model Failover Strategy.srt | 4.2 KB | ||
| 07. Introduction to Model Customization.mp4 | 4.6 MB | ||
| 07. Introduction to Model Customization.srt | 4.3 KB | ||
| 08. Parameter Efficient Model Customization.mp4 | 5.9 MB | ||
| 08. Parameter Efficient Model Customization.srt | 4.1 KB | ||
| 09. Deploying Customized Models with SageMaker.mp4 | 9.5 MB | ||
| 09. Deploying Customized Models with SageMaker.srt | 7.3 KB | ||
| 10. Demo Deploying a Customized Model with SageMaker.mp4 | 15.8 MB | ||
| 10. Demo Deploying a Customized Model with SageMaker.srt | 4.7 KB | ||
| 11. Model Lifecycle Management Part 1.mp4 | 6.4 MB | ||
| 11. Model Lifecycle Management Part 1.srt | 4.3 KB | ||
| 12. Model Lifecycle Management Part2.mp4 | 8.9 MB | ||
| 12. Model Lifecycle Management Part2.srt | 6.7 KB | ||
| 13. Automated Model Deployment Pipelines.mp4 | 9.5 MB | ||
| 13. Automated Model Deployment Pipelines.srt | 7.2 KB | ||
| 14. Model Governance and Change Control.mp4 | 6.5 MB | ||
| 14. Model Governance and Change Control.srt | 3.9 KB | ||
| 15. Module_Summary.mp4 | 12.2 MB | ||
| 15. Module_Summary.srt | 7.8 KB | ||
| 16. Sample Exam Question.mp4 | 14.3 MB | ||
| 16. Sample Exam Question.srt | 7.1 KB | ||
| analyze-requirements-and-design-genai-solutions-slides.pdf | 20.3 MB | ||
| demos.txt | 409.6 B | ||
| 01. About the AWS Generative AI Engineer Professional Certification.mp4 | 5.8 MB | ||
| 01. About the AWS Generative AI Engineer Professional Certification.srt | 3.6 KB | ||
| 02. Selecting Appropriate Foundation Models.mp4 | 10.3 MB | ||
| 02. Selecting Appropriate Foundation Models.srt | 7.3 KB | ||
| 03. FM Integration Patterns - RAG Workflows Part 1.mp4 | 13.7 MB | ||
| 03. FM Integration Patterns - RAG Workflows Part 1.srt | 9.1 KB | ||
| 04. FM Integration Patterns - RAG Workflows Part 2.mp4 | 6.6 MB | ||
| 04. FM Integration Patterns - RAG Workflows Part 2.srt | 4.5 KB | ||
| 05. Demo Building a RAG Workflow.mp4 | 19.1 MB | ||
| 05. Demo Building a RAG Workflow.srt | 6.4 KB | ||
| 06. FM Integration Patterns - Agentic Orchestration.mp4 | 7.6 MB | ||
| 06. FM Integration Patterns - Agentic Orchestration.srt | 6.1 KB | ||
| 07. FM Integration Patterns - Event Driven Workflows.mp4 | 6.6 MB | ||
| 07. FM Integration Patterns - Event Driven Workflows.srt | 4.3 KB | ||
| 08. FM Integration Patterns - Serverless Architectures Part 1.mp4 | 9.4 MB | ||
| 08. FM Integration Patterns - Serverless Architectures Part 1.srt | 6.1 KB | ||
| 09. FM Integration Patterns - Serverless Architectures Part 2.mp4 | 6.2 MB | ||
| 09. FM Integration Patterns - Serverless Architectures Part 2.srt | 4.7 KB | ||
| 10. Demo Technical Proof-of-concept Using Amazon Bedrock.mp4 | 18.7 MB | ||
| 10. Demo Technical Proof-of-concept Using Amazon Bedrock.srt | 6.9 KB | ||
| 11. Understanding AWS AppSync Use Cases.mp4 | 4.2 MB | ||
| 11. Understanding AWS AppSync Use Cases.srt | 3.1 KB | ||
| 12. Understanding AWS PrivateLink.mp4 | 7.4 MB | ||
| 12. Understanding AWS PrivateLink.srt | 4.3 KB | ||
| 13. Real Time Inference vs. Batch Processing.mp4 | 8.5 MB | ||
| 13. Real Time Inference vs. Batch Processing.srt | 5.9 KB | ||
| 14. Demo Real-time and Batch Inference with Amazon Bedrock.mp4 | 18.6 MB | ||
| 14. Demo Real-time and Batch Inference with Amazon Bedrock.srt | 6.7 KB | ||
| 15. Demo Prompt Management.mp4 | 6.1 MB | ||
| 15. Demo Prompt Management.srt | 2 KB | ||
| 16. Demo Using Agents for Task Automation.mp4 | 21.3 MB | ||
| 16. Demo Using Agents for Task Automation.srt | 6.9 KB | ||
| 17. The AWS Well-architected Framework GenAI Lense.mp4 | 11.4 MB | ||
| 17. The AWS Well-architected Framework GenAI Lense.srt | 3.4 KB | ||
| 18. GenAIOps on AWS.mp4 | 11.4 MB | ||
| 18. GenAIOps on AWS.srt | 9.2 KB | ||
| 19. Evaluating Performance.mp4 | 7.6 MB | ||
| 19. Evaluating Performance.srt | 5.6 KB | ||
| 20. Module Summary.mp4 | 14.6 MB | ||
| 20. Module Summary.srt | 9.8 KB | ||
| 21. Sample Exam Question.mp4 | 10.7 MB | ||
| 21. Sample Exam Question.srt | 5.8 KB |
AIP-C01: Foundation Model Integration, Data Management, and Compliance
https://WebToolTip.com
Released 7/2026
By Faye Ellis
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Advanced | Genre: eLearning | Language: English + subtitle | Duration: 7h 41m 25s | Size: 1.4 GB
Designing production-ready generative AI solutions on AWS demands strong architecture, robust data pipelines, and mature governance controls.
Designing production-ready generative AI solutions on AWS demands strong architecture, robust data pipelines, and mature governance controls. In this course, AWS Certified Generative AI Engineer Professional: Foundation Model Integration, Data Management, and Compliance, you’ll gain the ability to design, implement, and govern generative AI solutions using AWS services. First, you’ll explore how to analyze requirements and design generative AI solutions using AWS Well-Architected best practices. Next, you’ll discover how to prepare data pipelines for foundation model consumption, including implementing vector stores and configuring retrieval mechanisms. Finally, you’ll learn how to implement prompt engineering strategies and effective governance. When you’re finished with this course, you’ll have the skills and knowledge of GenAI solutions on AWS needed to take on the Foundation Model Integration, Data Management, and Compliance domain of the AWS Certified Generative AI Engineer Professional exam.
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 273.9 MB | freecoursewb | 1 month | 2 | 2 |
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